Finding an Unique and “Natural” Extension of the Expected Value That Takes a Finite Value for All Functions in Non-Shy Subset of the Set of All Functions

Bharath Krishnan

doi:10.20944/preprints202307.0560.v10

Submit preprint
How it Works
Instructions for Authors
Subject Areas
Advisory Board
screening preprints
About
Awards
Log in/Register

Instructions for Authors
Awards
About
FAQ
Submit Log in/Register

Share this article with

Create alert

Email:

Load new image

preprints.org > computer science and mathematics > analysis > doi: 10.20944/preprints202307.0560.v10

Preprint Concept Paper Version 10 Preserved in Portico This version is not peer-reviewed

Finding an Unique and “Natural” Extension of the Expected Value That Takes a Finite Value for All Functions in Non-Shy Subset of the Set of All Functions

Bharath Krishnan

Version 1 : Received: 9 July 2023 / Approved: 10 July 2023 / Online: 10 July 2023 (08:56:52 CEST)
Version 2 : Received: 10 July 2023 / Approved: 11 July 2023 / Online: 11 July 2023 (09:34:34 CEST)
Version 3 : Received: 11 July 2023 / Approved: 12 July 2023 / Online: 13 July 2023 (05:00:22 CEST)
Version 4 : Received: 13 July 2023 / Approved: 13 July 2023 / Online: 14 July 2023 (05:13:22 CEST)
Version 5 : Received: 17 July 2023 / Approved: 17 July 2023 / Online: 17 July 2023 (10:02:07 CEST)
Version 6 : Received: 17 July 2023 / Approved: 18 July 2023 / Online: 19 July 2023 (03:39:53 CEST)
Version 7 : Received: 21 July 2023 / Approved: 21 July 2023 / Online: 21 July 2023 (09:36:51 CEST)
Version 8 : Received: 22 July 2023 / Approved: 24 July 2023 / Online: 24 July 2023 (10:51:59 CEST)
Version 9 : Received: 12 December 2023 / Approved: 13 December 2023 / Online: 13 December 2023 (10:12:55 CET)
Version 10 : Received: 13 December 2023 / Approved: 15 December 2023 / Online: 15 December 2023 (04:57:26 CET)
Version 11 : Received: 19 December 2023 / Approved: 21 December 2023 / Online: 22 December 2023 (08:47:53 CET)
Version 12 : Received: 22 December 2023 / Approved: 25 December 2023 / Online: 27 December 2023 (09:33:43 CET)
Version 13 : Received: 28 December 2023 / Approved: 28 December 2023 / Online: 29 December 2023 (03:06:03 CET)
Version 14 : Received: 30 December 2023 / Approved: 3 January 2024 / Online: 3 January 2024 (05:33:34 CET)
Version 15 : Received: 3 January 2024 / Approved: 4 January 2024 / Online: 4 January 2024 (09:37:33 CET)
Version 16 : Received: 4 January 2024 / Approved: 5 January 2024 / Online: 5 January 2024 (10:07:41 CET)
Version 17 : Received: 9 February 2024 / Approved: 10 February 2024 / Online: 12 February 2024 (12:09:52 CET)
Version 18 : Received: 18 March 2024 / Approved: 19 March 2024 / Online: 19 March 2024 (12:46:40 CET)
Version 19 : Received: 23 March 2024 / Approved: 25 March 2024 / Online: 26 March 2024 (08:22:18 CET)
Version 20 : Received: 26 March 2024 / Approved: 26 March 2024 / Online: 27 March 2024 (09:10:36 CET)

How to cite: Krishnan, B. Finding an Unique and “Natural” Extension of the Expected Value That Takes a Finite Value for All Functions in Non-Shy Subset of the Set of All Functions. Preprints 2023, 2023070560. https://doi.org/10.20944/preprints202307.0560.v10 Krishnan, B. Finding an Unique and “Natural” Extension of the Expected Value That Takes a Finite Value for All Functions in Non-Shy Subset of the Set of All Functions. Preprints 2023, 2023070560. https://doi.org/10.20944/preprints202307.0560.v10

Cite

Export citation file: Bib TeX | RIS

MDPI and ACS Style

Krishnan, B. Finding an Unique and “Natural” Extension of the Expected Value That Takes a Finite Value for All Functions in Non-Shy Subset of the Set of All Functions. Preprints 2023, 2023070560. https://doi.org/10.20944/preprints202307.0560.v10

APA Style

Krishnan, B. (2023). Finding an Unique and “Natural” Extension of the Expected Value That Takes a Finite Value for All Functions in Non-Shy Subset of the Set of All Functions. Preprints. https://doi.org/10.20944/preprints202307.0560.v10

Chicago/Turabian Style

Krishnan, B. 2023 "Finding an Unique and “Natural” Extension of the Expected Value That Takes a Finite Value for All Functions in Non-Shy Subset of the Set of All Functions" Preprints. https://doi.org/10.20944/preprints202307.0560.v10

Abstract

Suppose for

Keywords

expected value; hausdorff measure; (Exact) dimension function; function space; prevalent and shy sets; entropy; choice function

Subject

Computer Science and Mathematics, Analysis

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download PDF

Comments (1)

Comment 1

Received: 15 December 2023
Commenter: Bharath Krishnan
Commenter's Conflict of Interests: Author

Comment: Added citation to the def. of anomaly. Converted M* to B*. (I request in eq. 4.3.2, to properly place the parenthesis around function K. Last time, it was too small.)

+ Respond to this comment

Not displayed online.

Importance: How significant is the paper to the field?

Outstanding/highlight paper

Significant contribution

Incremental contribution

No contribution

I am not qualified to judge

Soundness of evidence/arguments presented:

Conclusions well supported

Most conclusions supported (minor revision needed)

Incomplete evidence (major revision needed)

Hypothesis, unsupported conclusions, or proof-of-principle

I am not qualified to judge

Please leave your comment to this article below.

Mathematical equations can be typed in either LaTeX formats \\[ ... \\] or $$ ... $$, or MathML format <math> ... </math>. Try the LaTeX or MathML example.

Type equation:

Preview:

Copy equation into message below

Close menu

Please click a symbol to insert it into the message box below:

Please enter the link here:

Please enter a valid URL

Optionally, you can enter text that should appear as linked text:

Copy link into message below

Close menu

Please enter or paste the URL to the image here (please only use links to jpg/jpeg, png and gif images):

Please enter a valid URL

Copy image into message below

Close menu

Type author name or keywords to filter the list of references in this group (you can add a new citation under Bibliography):

No existing citations in Discussion Group

Wikify editor is a simple editor for wiki-style mark-up. It was written by MDPI for Sciforum in 2014. The rendering of the mark-up is based on Wiky.php with some tweaks. Rendering of mathematical equations is done with MathJax. Please send us a message for support or for reporting bugs.

Close menu

Please declare any conflicts of interest you may have with this paper, financial or otherwise.

I do not have a conflict of interest

I would like to declare a conflict of interest

Display my name on the website Send my name and email address to the authors

Captcha

Renew

I accept the following conditions:

Comments must follow the standards of professional discourse and should focus on the scientific content of the article. Insulting or offensive language, personal attacks and off-topic remarks will not be permitted. Comments must be written in English. Preprints reserves the right to remove comments without notice. Readers who post comments are obliged to declare any competing interests, financial or otherwise.

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)

* All users must log in before leaving a comment

what’s this?

Add a record of this review to Publons to track and showcase your reviewing expertise across the world’s journals.

Downloads 0

Comments 1

Metrics 0

Get PDF Cite Share 0

Bookmark BibSonomy Mendeley Reddit Delicious

Alerts

Notify me about updates to this article or when a peer-reviewed version is published.

Preprints.org is a free preprint server subsidized by MDPI in Basel, Switzerland.

MDPI Initiatives

SciProfiles
Sciforum
Encyclopedia
MDPI Books
Scilit
Proceedings
JAMS

Important links

How it Works
Advisory Board
FAQ
Friendly Journals
Instructions for Authors
About
Statistics

Choose the area that interest you and we will send you notifications of new preprints at your preferred frequency.

Disclaimer

We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.

RSS feed for

Preprints: The Multidisciplinary Preprint Platform

Paste the URL in your RSS reader:

https://www.preprints.org/rss

If you want to subscribe our website in subject-wide, you could find the URL by choosing in the following:

https://www.preprints.org/rss

Please note that by using ScienceDirect RSS feeds, you agree to our Terms of Use and Privacy Policy.