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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v15

A Solution of The Collatz Conjecture Problem

Baoyuan Duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture; (*3+1)/2^k odd sequence; (*3+2^m-1)/2^k odd sequence; (*3+2^m-1)/2^k odd tree.

Online: 10 April 2024 (09:37:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0504.v1

Robust Bias Compensation Method for Sparse Normalised Quasi-Newton Least-Mean with Variable-Mixing-Norm Adaptive Filtering

Ying-Ren Chien, Han-En Hsieh, Guobing Qian

Subject: Computer Science And Mathematics, Signal Processing Keywords: bias compensation; convex combination; impulse noise (IN); noisy inputs; variable mixed norm adaptive filtering algorithm

Online: 8 April 2024 (07:13:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0250.v1

Human Activity Recognition in a Free-Living Environment Using an Ear-Worn Motion Sensor

Lukas Boborzi, Julian Decker, Razieh Rezaei, Roman Schniepp, Max Wuehr

Subject: Computer Science And Mathematics, Signal Processing Keywords: human activity recognition; inertial sensor; ear; in-ear sensing; vital sign monitoring; wearables; machine learning; deep learning

Online: 3 April 2024 (11:06:45 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.0081.v1

Error Model of the Measurement Chain Containing the Discrete Wavelet Transform Algorithm

Marian Kampik, Jerzy Roj, Łukasz Dróżdż

Subject: Computer Science And Mathematics, Signal Processing Keywords: measurement chain error model; uncertainty estimation; discrete wavelet transform

Online: 2 April 2024 (02:27:20 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.1490.v1

SVM Dynamic Selection of Voting Rule for Cooperative Spectrum Sensing in CUAVNs

Chongyu Yu, Jin Shen, Jun Wu, Ruiyi Zheng, Mingkun Su, Lei Qiao, Jipeng Gan, and Weiwei Cao

Subject: Computer Science And Mathematics, Signal Processing Keywords: Unmanned aerial vehicle; cooperative spectrum sensing; voting rule; support vector machine; dynamic selection

Online: 26 March 2024 (08:18:22 CET)

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Preprint ARTICLE | doi:10.20944/preprints202403.0386.v1

Advanced Detection of Cardiac Beat Intervals in Functional Near-Infrared Spectroscopy(fNIRS) through Signal Integration Reconstruction

Kyoung soo Kim, Taehoon Kim, Jihyun Cha

Subject: Computer Science And Mathematics, Signal Processing Keywords: Heartbeat; fNIRS; RR-interval; heart rate; HRV; Cardiac beat interval; algorithm

Online: 8 March 2024 (01:52:57 CET)

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Preprint REVIEW | doi:10.20944/preprints202403.0082.v1

A Comprehensive Survey of Brain-Computer Interface Technology in Healthcare: Research Perspectives

Meenalosini Vimal Cruz, Suhaima Jamal, Sibi Chakkaravarthy Sethuraman

Subject: Computer Science And Mathematics, Signal Processing Keywords: Brain Computer Interface; Alzheime; Prosthetic Control; Neurofeedback; Human Computer Interaction

Online: 4 March 2024 (04:12:55 CET)

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Preprint ARTICLE | doi:10.20944/preprints202402.1466.v1

SALOS - A UWB Single Anchor Indoor Localization System based on a Statistical Multipath Propagation Model

Sven Ole Schmidt, Marco Cimdins, Fabian John, Horst Hellbrück

Subject: Computer Science And Mathematics, Signal Processing Keywords: single anchor localization; indoor localization; UWB; channel impulse response; multipath propagation model; optimal anchor positioning; signal processing; DW1000

Online: 26 February 2024 (14:24:22 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.1768.v1

Attention Mechanism and LSTM Network for Fingerprint-Based Indoor Location System

Zhen Wu, Peng Hu, Shuangyue Liu, Tao Pang

Subject: Computer Science And Mathematics, Signal Processing Keywords: fingerprinting; indoor localization system; long short-term memory (LSTM); self-attention mechanism

Online: 24 January 2024 (10:45:59 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.1250.v1

IoT Communication Based on MQTT and OneNET Cloud Platform in Big Data Environment

Youcheng Shan, Yuening Su, Jiahui Lin, Tingyu Shan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Big data environment; IoT; MQTT; OneNET Cloud platform

Online: 17 January 2024 (07:52:04 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0969.v1

Extended Guided Filter: Simultaneous Noise Suppression and Details Enhancement

Jian Li, Zhenping Sun

Subject: Computer Science And Mathematics, Signal Processing Keywords: Guided image filter; denoising; enhancement.

Online: 12 January 2024 (09:50:48 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0826.v1

Image Steganography and Style Transformation based on Generative Adversarial Network

Li Li, Xinpeng Zhang, Kejiang Chen, Guorui Feng, Deyang Wu, Weiming Zhang

Subject: Computer Science And Mathematics, Signal Processing Keywords: Generative Adversarial Network (GAN); image steganography; style transfer

Online: 10 January 2024 (10:55:12 CET)

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Preprint REVIEW | doi:10.20944/preprints202310.2032.v2

Mathematical and Statistical Review of NMR Time Domain Data Pre-Processing

Aixiang Jiang

Subject: Computer Science And Mathematics, Signal Processing Keywords: NMR; pre-processing; direct current offset removal; eddy current correction; weighting; domain transformation

Online: 8 January 2024 (14:05:37 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0379.v1

Adaptive Trajectories CFAR Mirror Filters and Elevation Angle Evaluation for MIMO Radar-Based Hand Gesture Recognition

Tzu-Jung Tseng, Jian-Jiun Ding

Subject: Computer Science And Mathematics, Signal Processing Keywords: MIMO radar; hand gesture recognition; adaptive signal processing algorithm; random forest; mirror filtering; elevation angle estimation

Online: 4 January 2024 (15:17:38 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0125.v1

Lung-DT: An AI-Powered Digital Twin Framework for Thoracic Health Monitoring and Diagnosis

Roberta Avanzato, Francesco Beritelli, Alfio Lombardo, Carmelo Ricci

Subject: Computer Science And Mathematics, Signal Processing Keywords: Digital twin; IoT sensors; image processing; lung healthcare; smart healthcare; convolutional neural network; deep learning

Online: 3 January 2024 (10:36:37 CET)

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The integration of Artificial Intelligence (AI) with Digital Twins (DTs) has emerged as a promising approach to revolutionize healthcare, particularly in the diagnosis and management of thoracic disorders. This study proposes a comprehensive framework, named Lung-DT, which leverages IoT sensors and AI algorithms to establish a digital representation of a patient’s respiratory health. Using the YOLOv8 neural network, the Lung-DT system accurately classifies chest X-Rays into five distinct categories of lung diseases, including "Normal," "Covid," "Lung Opacity," "Pneumonia," and "Tuberculosis". The system’s performance was evaluated on a chest X-Ray dataset, demonstrating an impressive average accuracy of 96.6% across all classes. Further tests (prediction) were conducted on the trained network using a third dataset available in the literature and completely unknown to the network, yielding an average accuracy of 98% across three classes. The proposed Lung-DT framework offers several advantages over conventional diagnostic methods. Firstly, it enables real-time monitoring of lung health through continuous data acquisition from IoT sensors, facilitating early diagnosis and intervention. Secondly, the AI-powered classification module provides automated and objective assessments of chest X-Rays, reducing dependence on subjective human interpretation. Thirdly, the twin digital representation of the patient’s respiratory health allows for comprehensive analysis and correlation of multiple data streams, providing valuable insights for personalized treatment plans. The integration of IoT sensors, AI algorithms, and DT technology within the Lung-DT system demonstrates a significant step towards improving thoracic healthcare. By enabling continuous monitoring, automated diagnosis, and comprehensive data analysis, the Lung-DT framework has enormous potential to enhance patient outcomes, reduce healthcare costs, and optimize resource allocation.

Preprint ARTICLE | doi:10.20944/preprints202312.2341.v1

An Innovative Information Hiding Scheme Based on Block-Wise Pixel Reordering

Jui‐Chuan Liu, Hengxiao Chi, Ching-Chun Chang, Chin‐Chen Chang

Subject: Computer Science And Mathematics, Signal Processing Keywords: data hiding; vector quantization; codebook; codeword index reordering

Online: 30 December 2023 (16:30:58 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.2194.v1

Directional Emphasis Filtering in Artifact Metrics for Rejecting Raster-Scanning-Created Clones

Akira Iwahashi, Naoki Yoshida, Tsutomu Matsumoto

Subject: Computer Science And Mathematics, Signal Processing Keywords: Artifact metrics; Clone resistance; Frequency filtering; Raster scanning; Copy detection; Counterfeit ;

Online: 28 December 2023 (14:42:34 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.1894.v1

A Fast ICI Based Adaptive Thresholding for Sparse Image Reconstruction Using a Matrix Based Wavelet Transformation

Ivan Volaric, Victor Sucic

Subject: Computer Science And Mathematics, Signal Processing Keywords: Compressive sensing; Fast intersection of confidence intervals; Image reconstruction; Iterative soft thresholding; Signal sparsity; Sparse reconstruction algorithm.

Online: 26 December 2023 (11:25:13 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.0633.v1

A Complete Pipeline for Heart Rate Extraction from Infant ECG

Harry T. Mason, Astrid Priscilla Martinez-Cedillo, Quoc C. Vuong, M. Carmen Garcia-de-Soria, Stephen Smith, Elena Geangu, Marina I. Knight

Subject: Computer Science And Mathematics, Signal Processing Keywords: ECG; Infant ECG; Heart Rate; R-Peaks; Open-Source; Naturalistic; Longform

Online: 8 December 2023 (14:39:00 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.0532.v1

Evaluating a 3D Ultrasound Imaging Resolution of Single Transmitter/Receiver with Coding Mask by Extracting Phase Information

Mohammad Syaryadhi, Eiko Nakazawa, Norio Tagawa, Ming Yang

Subject: Computer Science And Mathematics, Signal Processing Keywords: single transducer; coding mask; frequency subband compound; SCM

Online: 7 December 2023 (14:32:26 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v14

A Solution of The Collatz Conjecture Problem

Baoyuan Duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture; (*3+1)/2^k odd sequence; (*3+2^m-1)/2^k odd sequence; (*3+2^m-1)/2^k odd tree; weight function

Online: 21 November 2023 (10:43:13 CET)

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Preprint REVIEW | doi:10.20944/preprints202311.0644.v1

Mathematical and Statistical Review of NMR Frequency Domain Data Pre-processing

Aixiang Jiang

Subject: Computer Science And Mathematics, Signal Processing Keywords: NMR pre-processing; phase error correction; baseline correction; reference deconvolution; integration and quantification; normalization and transformation

Online: 9 November 2023 (14:22:18 CET)

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Preprint ARTICLE | doi:10.20944/preprints202311.0467.v1

Scaling Exponents of Time Series Data: A Machine Learning Approach

Sebastian Raubitzek, Luiza Corpaci, Kevin Mallinger, Rebecca Hofer

Subject: Computer Science And Mathematics, Signal Processing Keywords: Scaling Exponent; Hurst Exponent; Machine Learning; Artificial Intelligence; Complexity; Regression Analysis

Online: 8 November 2023 (01:42:42 CET)

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In this study, we present a novel approach to estimate the Hurst exponent of time series data using a variety of machine learning algorithms. The Hurst exponent is a crucial parameter in characterizing long-range dependence in time series, and traditional methods such as Rescaled Range (R/S) analysis and Detrended Fluctuation Analysis (DFA) have been widely used for its estimation. However, these methods have certain limitations, which we sought to address by modifying the R/S approach to distinguish between fractional Lévy and fractional Brownian motion, and by demonstrating the inadequacy of DFA and similar methods for data that resembles fractional Lévy motion. This inspired us to utilize machine learning techniques to improve the estimation process. In an unprecedented step, we train various machine learning models, including LightGBM, MLP, and AdaBoost, on synthetic data generated from random walks, namely fractional Brownian motion and fractional Lévy motion, where the ground truth Hurst exponent is known. Meaning that we can initialize and create these stochastic processes with a scaling Hurst/scaling exponent which, is then used as the ground truth for training. Furthermore, we perform the continuous estimation of the scaling exponent directly from the time series, without resorting to the calculation of the power spectrum or other sophisticated preprocessing steps, as done in past approaches. Our experiments reveal that the machine learning-based estimators outperform traditional R/S analysis and DFA methods in estimating the Hurst exponent, particularly for data akin to fractional Lévy motion. Validating our approach on real-world financial data, we observe a divergence between the estimated Hurst/scaling exponents and results reported in the literature. Nevertheless, the confirmation provided by known ground truths reinforces the superiority of our approach in terms of accuracy. This work highlights the potential of machine learning algorithms for accurately estimating the Hurst exponent, paving new paths for time series analysis. By marrying traditional finance methods with the capabilities of machine learning, our study provides a novel contribution towards the future of time series data analysis.

Preprint ARTICLE | doi:10.20944/preprints202311.0046.v1

Multi-DBN Weighted Voting Algorithm for Multi-Targets Classification in WSN

Heng Zhang, Yang Zhou

Subject: Computer Science And Mathematics, Signal Processing Keywords: WSN; multi-targets classification; DBN classifier; multi-DBN weighted voting algorithm

Online: 1 November 2023 (09:35:38 CET)

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Preprint REVIEW | doi:10.20944/preprints202310.2032.v1

Mathematical and Statistical Review of NMR Time Domain Data Pre-Processing

Aixiang Jiang

Subject: Computer Science And Mathematics, Signal Processing Keywords: NMR; pre-processing; direct current offset removal; eddy current correction; weighting; domain transformation

Online: 31 October 2023 (08:14:42 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v13

A Solution of The Collatz Conjecture Problem

baoyuan duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture; (*3+1)/2^k odd sequence; (*3+2^m-1)/2^k odd sequence; (*3+2^m-1)/2^k odd tree; weight function

Online: 30 October 2023 (09:47:16 CET)

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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v12

A Solution of The Collatz Conjecture Problem

baoyuan duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture; (*3+1)/2^k odd sequence; (*3+2^m-1)/2^k odd sequence; (*3+2^m-1)/2^k odd tree; weight function

Online: 17 October 2023 (07:08:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202310.0916.v1

Fast Converging Gauss-Seidel Iterative Algorithm for Massive MIMO Systems

Dong Shen, Li Chen, Qiang Li, Hao Liang

Subject: Computer Science And Mathematics, Signal Processing Keywords: Massive MIMO; Conjugate Gradient; Jacobi; Gauss-Seidel; Kronecker Channel

Online: 16 October 2023 (08:38:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v11

A Solution of The Collatz Conjecture Problem

baoyuan duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture; (*3+1)/2^k odd sequence; (*3+2^m-1)/2^k odd sequence; (*3+2^m-1)/2^k odd tree; weight function

Online: 21 September 2023 (03:25:23 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.0700.v1

Tensor-Train Decomposition Based Hybrid Beamforming for Millimeter-Wave Massive MIMO/FSO in UAV with RIS Networks

Xiaoping Zhou, Pengyan Feng, Jiehui Li, Jiajia Chen, Yang Wang

Subject: Computer Science And Mathematics, Signal Processing Keywords: UAV communication; FSO; massive MIMO; tensor decomposition; hybrid beamforming

Online: 11 September 2023 (12:07:03 CEST)

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Preprint REVIEW | doi:10.20944/preprints202308.1236.v1

Wearable Solutions for Stress Monitoring for Individuals with Autism Spectrum Disorder (ASD): Systematic Literature Review

Sandra Cano, Edgar Franco, Juan Apablaza, Matías García

Subject: Computer Science And Mathematics, Signal Processing Keywords: wearable technology; autism spectrum disorder; physiological signals

Online: 17 August 2023 (12:59:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v10

A Solution of The Collatz Conjecture Problem

baoyuan duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture; (*3+1)/2^k odd sequence; (*3+2^m-1)/2^k odd sequence; (*3+2^m-1)/2^k odd tree; weight function

Online: 11 August 2023 (03:01:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.0695.v1

Magnetoencephalogram Network Analysis of Depression Based on Polynomial Kernel Granger Causality

Yijia Ma, Jing Qian, Qizhang Gu, Wanyi Yi, Wei Yan, Jianxuan Yuan, Jun Wang

Subject: Computer Science And Mathematics, Signal Processing Keywords: Brain network; Magnetoencephalogram; Granger causality; Kernel function

Online: 9 August 2023 (05:11:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201908.0320.v2

Persistence Landscape based Topological Data Analysis for Personalized Arrhythmia Classification

Yu-Shi Liu, Lei Wang, Jian Cen, Qiu-Hua Liu, Yan Yan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Electrocardiography Analysis; Persistence Landscape; Signal Analysis; Machine Learning; Topological Data Analysis; Topological Signal Signature; Classification; Time Series Analysis; Biomedical Signal Analysis; Persistence Homology

Online: 2 August 2023 (10:33:09 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.2084.v1

Non-Cooperative Spectrum Sensing Strategy based on Recurrence Quantification Analysis in the Context of the Cognitive Radio

Jean-Marie KADJO, Koffi YAO, Ali MANSOUR, Denis JEUNE

Subject: Computer Science And Mathematics, Signal Processing Keywords: cognitive radio; dynamic spectrum access; spectrum sensing; embedding parameters; false nearest neighbours; recurrence quantification analysis

Online: 31 July 2023 (10:08:43 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.1973.v1

Motor Imagery Classification Using Trial Extension in Spatial Domain with Rhythmic Components of EEG

Md. Khademul Islam Molla, Sakir Ahamed, Ahmed M. M. Almassri, Hiroaki Wagatsuma

Subject: Computer Science And Mathematics, Signal Processing Keywords: brain computer interface; classification; electroencephalography; motor imagery task; subband decomposition

Online: 28 July 2023 (11:19:47 CEST)

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Preprint COMMUNICATION | doi:10.20944/preprints202307.1896.v1

Pre-training of Multi-order Acoustic Simulation for Replay Voice Spoofing Detection

Changhwan Go, Nam In Park, Oc-Yeub Jeon, Chanjun Chun

Subject: Computer Science And Mathematics, Signal Processing Keywords: voice spoofing; acoustic configuration; deep learning

Online: 28 July 2023 (10:14:32 CEST)

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Voice spoofing attempts to break into a specific automatic speaker verification (ASV) system by forging the user’s voice, and can be used through methods, such as text-to-speech (TTS), voice conversion (VC), and replay attacks. Recently, deep learning-based voice spoofing countermeasures have been developed. however, the problem with replay is that it is difficult to construct a large number of datasets because it requires a physical recording process. To overcome these problems, this study proposes a pre-training framework based on multi-order acoustic simulation for replay voice spoofing detection. Multi-order acoustic simulation utilizes existing clean signal and room impulse response (RIR) datasets to generate audios, which simulate the various acoustic configurations of the original and replayed audios. The acoustic configuration refers to factors, such as the microphone type, reverberation, time delay, and noise that may occur between a speaker and microphone during the recording process. We assume that a deep learning model trained on an audio that simulates the various acoustic configurations of the original and replayed audios can classify the acoustic configurations of the original and replay audios well. To validate this, we performed pre-training to classify the audio generated by the multi-order acoustic simulation into 3 classes: clean signal, audio simulating the acoustic configuration of the original audio, and audio simulating the acoustic configuration of the replay audio. We also set the weights of the pre-training model to the initial weights of the replay voice spoofing detection model using the existing replay voice spoofing dataset and then performed fine-tuning. To validate the effectiveness of the proposed method, we evaluated the performance of the conventional method without pre-training and proposed method using an objective metric, i.e., the accuracy. As a result, the conventional method achieved 92.94% accuracy and proposed method achieved 98.16% accuracy.

Preprint ARTICLE | doi:10.20944/preprints202301.0541.v9

A Solution of The Collatz Conjecture Problem

baoyuan duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture; (*3+1)/2^k odd sequence; (*3+2^m-1)/2^k odd sequence; (*3+2^m-1)/2^k odd tree; weight function

Online: 21 July 2023 (08:53:32 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.1436.v1

Target Tracking Limits in a Dense Clutter Environments

Zvonko Radosavljevic, Dejan Ivkovic, Branko Kovacevic

Subject: Computer Science And Mathematics, Signal Processing Keywords: multi target tracking; false track discrimination; radar; probability of detection

Online: 21 July 2023 (02:34:08 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.1022.v1

Analyses of Subsample Averaging of Single Trials for Event-Related Potential Classification

Xiaoqian Chen, Lalit Gupta

Subject: Computer Science And Mathematics, Signal Processing Keywords: ERP classification; single trial averaging; interclass separation; convolution neural networks; support vector machines.

Online: 17 July 2023 (02:32:36 CEST)

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Event-related potentials (ERPs) are estimated by averaging time-locked single trial electroencephalography (EEG) signals in response to specific events or stimuli. Classifying ERPs accurately is a challenge because (a) single trials have poor signal-to-noise-ratios (SNRs) and (b) it is difficult to collect large single trial ensembles to generate high SNR ERPs for classifier training and testing. The m-subsample averaging (m-SA) strategy which generates small-sample ERPs by repeated averaging of a small number of single trials drawn without replacement, has been proposed as a solution to the two problems. An ERP formed by averaging m single trials is referred to as an m-ERP where m is referred to as the averaging parameter. In this study, we conduct thorough analyses of m-SA and focus on issues not addressed in previous studies to better understand the beneficial properties of m-SA and to further support its application for ERP classification. Specifically, we (a) analyze the improvement in SNR as a function of m using the mean-root-mean-square SNR and visual analyses of m-ERP plots with confidence intervals, (b) analyze the improvement in interclass separation as a function of m, (c) determine how the SNR and interclass separation analyses can help to select the averaging parameter m, (d) determine the number of distinct m-ERPs that can be drawn from a single-trial ensemble, and (e) determine several probabilities related to the generation of distinct m-ERPs. Furthermore, an extensive set of experiments are designed to analyze the performance of support vector machine and convolution neural network classifiers employing m-SA with various combinations of the averaging parameters used for generating the training and test sets. The results confirm that ERPs can be classified accurately using small subsample averaging. Most importantly, it is concluded that m-SA can be deployed in practice to accurately classify ERPs in brain activity research and in clinical applications without having to collect a prohibitively large number of single trials.

Preprint ARTICLE | doi:10.20944/preprints202307.0885.v2

Design of Semantic Understanding System for Optical Staff Symbols

Fengbin Lou, Yaling Lu, Guangyu Wang

Subject: Computer Science And Mathematics, Signal Processing Keywords: semantic understanding; neural networks; optical music recognition; YOLOv5; digital code

Online: 13 July 2023 (08:50:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.0885.v1

Design of Semantic Understanding System for Optical Staff Symbols

Fengbin Lou, Yaling Lu, Guangyu Wang

Subject: Computer Science And Mathematics, Signal Processing Keywords: semantic understanding; neural networks; optical music recognition; YOLOv5; digital code

Online: 13 July 2023 (05:07:42 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v8

A Solution of The Collatz Conjecture Problem

baoyuan duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture; (*3+1)/2^k odd sequence; (*3+2^m-1)/2^k odd sequence; (*3+2^m-1)/2^k odd tree; weight function

Online: 25 June 2023 (04:40:44 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.1039.v1

Design and Simulation of Soft Decision Decoding Based on Chaotic M-ary Spread Spectrum System

Ruopeng Liu, Pengyi Wang, Xiduo Wang

Subject: Computer Science And Mathematics, Signal Processing Keywords: M-ary Spread Spectrum; Chaotic Spreading Sequence; (CD)2MA; FHP-BP Decoding Algorithm; BER

Online: 14 June 2023 (09:56:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0922.v1

MRI Image Fusion Based on Sparse Representation with Patch-based Multiple Salient Features Measurement

Qiu Hu, Weiming Cai, Shuwen Xu, Shaohai Hu

Subject: Computer Science And Mathematics, Signal Processing Keywords: Multimodality medical image; Image fusion; Sparse representation (SR); Kronecker criterion; Activity level measure

Online: 13 June 2023 (10:09:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0740.v1

Comparison of Bootstrap Methods for Estimating Causality in Linear Dynamic Systems: A Review

Fumikazu Miwakeichi, Andreas Galka

Subject: Computer Science And Mathematics, Signal Processing Keywords: Causal analysis; Granger Causality; Bootstrap methods; Multivariate time series; Impulse response function

Online: 12 June 2023 (03:14:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0321.v2

OculusGraphy: Signal Analysis of the Electroretinogram in a Rabbit Model of Endophthalmitis Using Discrete and Continuous Wavelet Transforms

Aleksei Zhdanov, Paul Constable, Sultan Mohammad Manjur, Anton Dolganov, Hugo F. Posada-Quintero, Aleksander Lizunov

Subject: Computer Science And Mathematics, Signal Processing Keywords: biomedical research; electroretinography; electroretinogram; ERG; electrophysiology

Online: 19 May 2023 (07:16:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.1275.v1

A Lightning Warning Method Using Atmospheric Electric Field Based on EEWT-ASG and Morpho

Xiang Li, Ling Yang, Qiyuan Yin, Zhipeng Yang, Fangcong Zhou

Subject: Computer Science And Mathematics, Signal Processing Keywords: Atmospheric electric field (AEF); lightning risk warning; enhanced empirical Wavelet transform-Adaptive Savitzky Golay filter (EEWT-ASG); one-dimensional morphology; Wavelet transform (WT)

Online: 30 April 2023 (23:56:56 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0342.v1

On the Challenges of Acoustic Energy Mapping Using a WASN: Synchronization and Audio Capture

Emiliano E. García-Unzueta, Caleb Rascon, Paul E. Mendez-Monroy

Subject: Computer Science And Mathematics, Signal Processing Keywords: wireless acoustic sensor network; synchronization; beamforming; acoustic mapping.

Online: 14 April 2023 (03:47:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0321.v1

OculusGraphy: Comparison Between Human and Rabbit Electroretinogram Based on Time-Domain and Time-Frequency Domain Analysis

Aleksei Zhdanov, Paul Constable, Sultan Mohammad Manjur, Anton Dolganov, Hugo F. Posada-Quintero, Aleksander Lizunov

Subject: Computer Science And Mathematics, Signal Processing Keywords: biomedical research; electroretinography; electroretinogram; ERG; electrophysiology

Online: 13 April 2023 (11:01:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v7

A Solution of The Collatz Conjecture Problem

baoyuan duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture; (*3+1)/2k odd sequence; (*3+2m-1)/2k odd sequence; (*3+2m-1)/2k odd tree; weight function

Online: 11 April 2023 (03:28:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v6

A Solution of The Collatz Conjecture Problem

baoyuan duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: Collatz conjecture, (*3+1)/2^k odd sequence, (*3+2^m-1)/2^k odd sequence, (*3+2^m-1)/2^k odd tree, weight function

Online: 3 April 2023 (07:22:34 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0541.v5

A Solution of The Collatz Conjecture Problem

baoyuan duan

Subject: Computer Science And Mathematics, Signal Processing Keywords: collatz conjecture; (*3+1)/2k odd sequence; (*3+2m-1)/2k odd sequence; (*3+2m-1)/2k odd tree; weight function ;

Online: 28 March 2023 (05:32:08 CEST)

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Preprint REVIEW | doi:10.20944/preprints202302.0052.v1

Reducing Noise, Artifacts and Interference in Single-Channel EMG Signals : A Review

Marianne Boyer, Laurent Bouyer, Jean-Sébastien Roy, Alexandre Campeau-Lecours

Subject: Computer Science And Mathematics, Signal Processing Keywords: Electromyography; Artifact; Noise; interference; Contaminant reduction; Signal processing; Denoising; Filtering

Online: 3 February 2023 (02:50:48 CET)

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Preprint ARTICLE | doi:10.20944/preprints202212.0543.v1

Playing Blackjack Using Computer Vision

Tauheed Khan Mohd, Anas Akkar, Justin Cassens, Samuel Cregan, Maame Araba Vander-Pallen

Subject: Computer Science And Mathematics, Signal Processing Keywords: OpenCV; Python; objects; object detection; card

Online: 28 December 2022 (12:42:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints202108.0574.v2

Variational Anisotropic Gradient-Domain Image Processing

Ivar Farup

Subject: Computer Science And Mathematics, Signal Processing Keywords: variational methods; anisotropic diffusion; gradient-domain image processing; local contrast enhancement

Online: 24 September 2021 (10:24:26 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202108.0574.v1

Variational Anisotropic Gradient-Domain Image Processing

Ivar Farup

Subject: Computer Science And Mathematics, Signal Processing Keywords: variational methods; anisotropic diffusion; gradient-domain image processing; local contrast enhancement

Online: 31 August 2021 (12:44:20 CEST)

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Preprint CONCEPT PAPER | doi:10.20944/preprints202106.0509.v2

A Novel Approach to Learning Models on EEG Data Using Graph Theory Features - A Comparative Study

Bhargav Prakash, Gautam Kumar Baboo, Veeky Baths

Subject: Computer Science And Mathematics, Signal Processing Keywords: EEG; Emotional States; Working Memory; Depression; Anxiety; Graph Theory; Classification; Machine Learning; Neural Networks.

Online: 6 July 2021 (12:42:59 CEST)

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Preprint ARTICLE | doi:10.3390/sci2010006

Making Japenese Ukiyo-e Art 3D in Real-Time

Innes Brown, Ognjen Arandjelović

Subject: Computer Science And Mathematics, Signal Processing Keywords: rendering; graphics; heritage; Japanese; Asian

Online: 28 February 2020 (00:00:00 CET)

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Preprint ARTICLE | doi:10.20944/preprints201610.0075.v1

EEG Signal Recognition Based on Wavelet Transform and ACCLN Network

Xuebin Qin, Jun Deng, Mei Wang, Yizhe Zhang, Pai Wang

Subject: Computer Science And Mathematics, Signal Processing Keywords: BCI; recognition; feature extraction; ACCLN network; RBF network

Online: 19 October 2016 (10:09:19 CEST)

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Computer Science and Mathematics