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在shannon entropy這個產品中，有3篇Facebook貼文，粉絲數超過7萬的網紅iThome，也在其Facebook貼文中提到， 如果我們想要透過波函數塌縮演算來實現無限的拼接，可選擇最小夏農熵（Shannon entropy）位置來進行塌縮，目的是選擇狀態數量最少，較穩定的位置，以減少拚接失敗的可能性 https://www.ithome.com.tw/voice/143323 ---------------------...

shannon entropy 在 iThome Facebook 的精選貼文

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2021-04-05 19:50:08 有 8 人按讚
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如果我們想要透過波函數塌縮演算來實現無限的拼接，可選擇最小夏農熵（Shannon entropy）位置來進行塌縮，目的是選擇狀態數量最少，較穩定的位置，以減少拚接失敗的可能性

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shannon entropy 在 iThome Facebook 的最佳貼文

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2021-03-27 19:53:42 有 6 人按讚
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如果我們想要透過波函數塌縮演算來實現無限的拼接，可選擇最小夏農熵（Shannon entropy）位置來進行塌縮，進一步減少拚接失敗的可能性

https://www.ithome.com.tw/voice/143323

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★ CyberTalent Connect 資安新鮮人才專區 🙋
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shannon entropy 在 李開復 Kai-Fu Lee Facebook 的精選貼文

李開復 Kai-Fu Lee By 李開復 Kai-Fu Lee

2020-05-21 11:11:13 有 527 人按讚
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分享亞勤的精彩演講。這是他上周在哥倫比亞大學工學院2020畢業典禮演講。他稱為是絕對是最大的“熵”的一屆畢業生。

本文來自人工智能學家微信公眾號
……………………………………

張亞勤2020寄語哥倫比亞大學畢業生：引領未知時代

2020年5月18日，人工智慧和數位視訊的世界級科學家和企業家，美國藝術與科學院院士、百度前總裁、清華大學智慧科學講席教授張亞勤博士，在哥倫比亞大學工程學院的畢業典禮上發表了主題演講。

張亞勤說:“面對全球疫情，技術成為最關鍵的變革力量，高速網路、軟體和人工智慧等基礎技術塑造我們生活、學習、工作和娛樂方式。”他提到：“隨著世界進入一個充滿挑戰和不確定性的新階段，年輕工程師迎來了回應歷史使命的決定性時刻，不僅要以技術創新，還要以同理心、勇氣和人文主義精神來迎接使命。”

哥倫比亞大學工程學院院長瑪麗·博伊斯(MaryC. Boyce)表示:“我們很高興能請到張亞勤博士(Dr.Ya-Qin Zhang)給我們的畢業生做演講，以此來紀念這一重要的里程碑。”她談到：“我們的畢業生將進入一個變化的世界，他們也將成為時代變化的締造者。學生們將受益張亞勤博士的觀點，其非凡職業道路也將鼓舞學生們。”（引用哥倫比亞大學新聞報導）

以下為百度前總裁、清華大學智慧科學講席教授張亞勤在2020年哥倫比亞大學工程學院畢業典禮上的致辭全文：

尊敬的Bollinger校長, Boyce院長，家長們，同學們，大家好。
我很榮幸能夠在這個非常時期，以特殊的形式出席這次特別的典禮。首先，恭喜2020屆畢業生，對你們取得的傑出成就表示衷心祝賀。你們做到了！

我也是一名哥倫比亞大學的學生家長。我的兒子現在哥大工學院二年級學生，我女兒是哥大商學院2020屆的畢業生。我想與所有家長分享這份難以言表的喜悅和驕傲，我們都做到了！

這無疑是我們有生記憶以來最具挑戰性和不確定性的一個時期。

我們不僅看到了科技創新的極速進步和第四次工業革命的巨大力量，人工智慧、納米技術、量子電腦和5G通信等等技術不斷突破。

我們還目睹了百年一遇的流行疾病在全球範圍內帶來的突發性破壞和災難性影響，對我們的社會基礎、經濟結構和生活方式帶來挑戰。

對於那些學習過熱力學第二定律的人來說，“熵”這個術語一定不陌生，它表示動態系統中的混沌程度(Chaos)。資訊理論的創始者Claud Shannon將這一概念擴展到了資訊的不確定性和隨機性。可以說，2020屆畢業生是被賦予“熵”值最高的一屆。未來的不可預測和混沌程度都是前所未有的。對你們如此，對我們所有人也是如此。

與你們的交流令我回想起我的學生時代和年輕時的工程師工作經歷。1990年畢業後，我的第一份工作是開發演算法，壓縮圖像和視頻，完成遠端傳輸，對國際標準MPEG和H.26x做出一點小貢獻：MPEG和H.26x也是如今Netflix、YouTube、Skype和Zoom等流行視頻應用程式的重要基礎。在過去的三十年裡，我有幸一直在激動人心的創新技術中徜徉， HDTV、自動駕駛、人工智慧和雲計算等等。在這一路走來，收穫的不僅是無窮的樂趣，也有超凡的艱辛。我想跟同學們分享我的三個體會：

1）在數據爆炸和不斷變化的世界中，成為具備強適應能力的學習者。在瞬息萬變的技術行業中，五年前學到的知識大多已無用處。你們在哥倫比亞大學中學習到最有價值的是學習新知的能力，是從繁雜噪音中分別信號的能力，是從眾多數據中提取“熵”的能力。我有一個行之有效的習慣，每天早上花10分鐘，找出對我而言最新的發現或最重要的3件事情，當天來學習。

2) 要擁有獨特的觀點和視角。當你們進入現實世界，會自然而然的開始被“打磨”，去遵循已有的趨勢，融入他人。我懇請你們保持自己的尖銳、棱角和與眾不同。當我與年輕工程師面聊時，我期待他們的觀點、他們的“熵”、他們鮮活的想法，這些遠比圓滑、打磨、“正確”要重要得多。

3) 無論做什麼事情，要秉承道德和人性。兩千多年前，偉大的希臘思想家蘇格拉底將道德作為追求真理的靈魂。大約同一時期，偉大的中國哲學家孔子把人性的“仁義”作為社會結構的基礎。在截然不同的文化下，兩位偉大思想家所見略同，並非巧合。今天，當我們面臨更多選擇、迷茫和誘惑時，這一點就變得更加重要。技術是中立的，但創新者是有使命的。技術是工具，但技術人員是為人類服務的。院長Mary Boyce對哥倫比亞工學院提出的願景“技術以人為本”是工程學的核心，也是我們工程師和技術人員的宗旨。

年輕的朋友們，對你們而言，這是一個決定性的時刻，請盡情的用你們的才華、激情和創新，更用你們的同理心，勇氣和人性，去展現，去閃耀，回應使命的召喚！

再次恭喜你們，2020屆畢業生！

以下是哥倫比亞大學對張亞勤作為畢業生典禮發言人的報導和過往成就的介紹
https://engineering.columbia.edu/news/class-day-2020-ya-qin-zhang

人工智慧和數位視訊的世界級科學家和企業家，百度前總裁張亞勤於2020年5月18日，在哥倫比亞大學工程學院的畢業典禮上發表主題演講。因為疫情的緣故，演講和畢業典禮將採取提前錄製形式，發送給全球的畢業生及其家人。

百度作為科技巨頭，向全球超過20億人提供包括移動互聯網和雲計算等服務，張亞勤曾負責智慧駕駛、雲計算、新興業務和公司的技術部門。是一位廣受讚譽的科學家和技術專家和創新領導者。他是聯合國、世界經濟論壇和許多公共論壇的領導人和發言人，積極討論新技術對社會變革性的影響以及如何縮小數位鴻溝。2018年，他帶領百度成為第一家加入國際人工智慧道德組織AI (PAI)的中國公司，目前也是全球最大自動駕駛開源平臺Apollo理事會的主席。

張亞勤說:“面對全球疫情，技術成為最關鍵的變革力量，高速網路、軟體和人工智慧等基礎技術塑造我們生活、學習、工作和娛樂方式。”他提到：“隨著世界進入一個充滿挑戰和不確定性的新階段，年輕工程師迎來了回應歷史使命的決定性時刻，不僅要以技術創新，還要以同理心、勇氣和人文主義精神來迎接使命。”

加入百度之前，張亞勤擔任了16年Microsoft的高管，任公司全球資深副總裁和微軟亞州研究院院長。2011年，他在中國創立了微軟風險投資加速器(Microsoft VentureAccelerator)。作為中國最有活力的創業引擎之一，該加速器已經幫助孵化了200多家公司。

張亞勤將在7月加入清華大學，擔任AI科學講席教授，並創立智慧產業研究院（AIR），將專注於第四次工業革命中的技術，包括自動駕駛，人工智慧、物聯網以及神經網路計算。

哥倫比亞大學工程學院院長瑪麗·博伊斯(MaryC. Boyce)表示:“我們很高興能請到張亞勤博士(Dr.Ya-Qin Zhang)給我們的畢業生做演講，以此來紀念這一重要的里程碑。”她談到：“在這個非凡的時代，沒有人能夠更好地講述技術在我們生活中扮演的角色，來描述技術在創造一個更緊密、更安全、更有創造力的人類社會中的潛力。無論工作還是社交，我們比以往任何時候都更加依賴技術來保持聯繫，我們的畢業生將進入一個變化的世界，他們也將成為時代變化的締造者。學生們將受益張亞勤博士的觀點，其非凡職業道路也將鼓舞學生們。”

張亞勤在12歲進入中國科技大學少年班，並獲得電氣工程學士和碩士學位。之後前往美國獲得喬治華盛頓大學的理學博士學位。他畢業于哈佛大學高管商業課程，在職業生涯的早期，曾擔任新澤西州普林斯頓（現為SRI）的Sarnoff Corp多媒體實驗室總監，還曾是GTE Labs（現為Verizon）的高級技術人員。

張亞勤是美國藝術與科學院院士和澳大利亞國家工程院院士。

1997年，年僅31歲的他，成為有史以來最年輕的科學家，被任命為IEEE會士。他撰寫了550多篇論文、12本書，並獲得了62項美國專利，為視頻編碼、流媒體、互聯網服務等領域的演算法和理論制定了全球標準。被IT時報、CNBC、《商業週刊》和全球商務評為亞洲十大CEO、年度CEO、50位全球傑出人物和十大創新者。

張亞勤博士是哥倫比亞工學院2022屆學生和2020屆商學院畢業生的家長，他同時還是哥倫比亞工學院訪問委員會的成員，也是哥倫比亞商學院的高級學者。

張亞勤哥倫比亞大學畢業典禮演講英文原文：

Leading in times ofuncertainty
President Bollinger, Dean Boyce, Parentsand Students:
I am honored to be here at this veryspecial occasion, at a very special time, in the most special form. First, abig congratulation to the class of 2020 for your remarkable accomplishments. Youmade it!
I am also a proud parent of Columbia.My son is a rising junior at the engineering school, and my daughter is also aclass 2020 for the business school. I share the immense joy and incrediblepride with all the parents, we all made it too!
This is undoubtedly the mostchallenging and uncertain time in our living memory.
We see the staggering pace ofinnovation and the transformative power of the fourth industrial revolution,with technology breakthroughs such as artificial intelligence, nano-technology,quantum computing, and 5G advanced communications.
We also see the sudden disruption andcatastrophic impact of the once-in-a-century pandemic at a global scale thatchallenges the very foundation of our social fabric, economic structure, andlife style.
For those of you who have learned the 2ndlaw of thermodynamics, you know the term “entropy”, which represents degree of chaosin a dynamic system. Claud Shannon, the founding father of information theory,extended this notion to measure information uncertainty and randomness. It’s fair to say that the Class of 2020 is the one that is “given” the highest entropy. The level ofunpredictability and chaos is unprecedented for you -- and for all of us.
Talking with you reminds me of my earlyyears as a student and young engineer. My first job after graduation in 1990was developing algorithms to compress imagery and video for remote transmission,essentially to extract the maximum entropy. The work eventuallycontributed in a small way to a set of international standards known as MPEGand H.26x, the base for today’s popular video applications used in Netflix, YouTube, Skype andZoom. Over last three decades, I had the distinct opportunity to work on someof the most exciting technologies such as HDTV, autonomous driving, AI, and cloudcomputing. I have had the wildest ride with not only a great deal of fun, butalso extraordinary hardship along the way. Let me share with you three of mypersonal learnings:
1) Be an adaptive learner in the world of dataexplosion and constant change. In today’s fast changing technology industry, most of what you learned fiveyears ago is irrelevant. The most valuable skill you’vegained at Columbia is the ability to learn new things, to discern the signalfrom the noise, and to extract entropy from the ocean of data. One routine Ifind particularly helpful is to commit just 10 minutes each morning and prioritize3 things – anything new and important to me – to learn that day.
2) Have a unique point of view and perspective. When you get into the realworld, there is a natural tendency to become “polished”, to follow existing trends, and toblend in with the rest.
I ASK you tomaintain your sharpness, your edge, and your differences. When I interviewpeople, particularly young engineers, I look for their point of view, theirentropy, and their flash of ideas, which to me is far more important than beingsmooth, polished or “correct”.
3) Hold Ethics and humanity at theheart of what you do. Over 2000 years ago, the great Greek thinker Ｓock-ruh-tease put ethics as the soul forthe pursuit of truth. Around the same time, the great Chinese philosopher Confuciusplaced “Renyi”, whichessentially means humanity, as the foundation for social structure. It is nocoincidence that two of the greatest minds from vastly different cultures hadthe same idea. This has become even more critical today as we all face morechoices, confusion, and temptations. Technology is neutral, but innovatorshave purpose. Engineering is a tool, but engineers serve humanity. “Engineering for Humanity”, the vision set byDean Mary Boyce for Columbia engineering is the very core of engineering andwhat engineers are all about.
My youngfriends, this is the defining moment for you, for you to rise, to shine andanswer the historic call of duty, with not only your talent, spark andinnovations, but also compassion, courage and humanity.
Congratulations again, Class 2020 !

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李開復 Kai-Fu Lee

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#1. 熵(資訊理論) - 維基百科，自由的百科全書

在1948年，克勞德·艾爾伍德·夏農將熱力學的熵，引入到資訊理論，因此它又被稱為夏農熵(Shannon entropy)。 目次. 1 簡介. 1.1 熵的計算.

#2. 從計算機編碼的角度看Entropy - HackMD

Shannon Entropy. 簡介. Entropy概念最早被用於熱力學，在1948年由Shannon將此概念引入 ...

#3. 決策不確定之衡量—Shannon 熵之應用

This research adapted the essence of Shannon's entropy model to infer the decision entropy model and measure the degree of decision uncertainty as research ...

#4. 資訊熵| Blog

熵(粵音商)(entropy)原本是物理學的概念，代表的是事物混亂的程度：熵愈高，事愈亂。資訊理論(Information Theory)之父夏農(Claude Shannon)於1948 年 ...

#5. Shannon Entropy - an overview | ScienceDirect Topics

The most important concept in Information Theory is Shannon's Entropy, which measures the amount of information held in data. Entropy quantifies to what extent ...

#6. The intuition behind Shannon's Entropy | by Aerin Kim

Shannon's Entropy leads to a function which is the bread and butter of an ML practitioner — the cross entropy that is heavily used as a loss function in ...

#7. Shannon entropy - Wiktionary

NounEdit ... where pi is the probability of character number i appearing in the stream of characters of the message. ... , so the circuit reduces (or "orders") the ...

#8. Shannon entropy | iThome

如果我們想要透過波函數塌縮演算來實現無限的拼接，可選擇最小夏農熵（Shannon entropy）位置來進行塌縮，進一步減少拚接失敗的可能性. 2021-03-25.

#9. Shannon entropy: a rigorous notion at the crossroads between ...

Statistical entropy was introduced by Shannon as a basic concept in information theory measuring the average missing information in a random source.

#10. Shannon entropy: axiomatic characterization and application

We have presented a new axiomatic derivation of Shannon entropy for a discrete probability distribution on the basis of the postulates of additivity and ...

#11. Shannon entropy - 英中– Linguee词典

大量翻译例句关于"Shannon entropy" – 英中词典以及8百万条中文译文例句搜索。

#12. [2105.12829] Estimating the variance of Shannon entropy - arXiv

... the multinomial case, the statistical properties of an estimator of a parameter that describes the variance of the plug-in estimator of Shannon entropy.

#13. Shannon entropy of partially polarized and partially coherent ...

Since the Shannon entropy is a standard measure of disorder, it is a useful quantity to characterize the randomness between the electric fields at two points in ...

#14. Analysis of digitized waveforms using Shannon entropy

A novel symbol‐oriented, information‐theoretic approach to signal analysis is described based on application of Shannon entropy. It is shown that this can ...

#15. A Shannon entropy analysis of immunoglobulin and T cell ...

In 1970, before any antigen-bound immunoglobulin structure had been solved, Elvin Kabat proposed that regions of high amino acid diversity would be the ...

#16. Shannon Entropy Diversity Metric | INDDEX Project

Whereas the Shannon Entropy Diversity Metric measures this in terms of distribution of individual foods, MFAD measures this in terms of nutrients. As a measure ...

#17. Shannon Entropy for Quantifying Uncertainty and Risk in ...

economic disparity. The rest of the article is organized as follows. Section 2 discusses measure theory and introduces. Shannon entropy, showcasing its ...

#18. Shannon Entropy Calculator | Information Theory

Shannon entropy, also known as information entropy or the Shannon entropy index, is a measure of the degree of randomness in a set of data. It ...

#19. Shannon Entropy

Shannon Entropy, like it's namesake, is not easily defined. As dark as it is light, as poppy as it is rocky, and as challenging as it is listenable, Shannon ...

#20. 香农熵_百度百科

中文名: 香农熵; 外文名: Shannon entropy; 实 质: 信息不确定性的多少. 提出时间: 1948年; 解决问题: 解决了对信息的量化度量问题; 应用学科: 通信工程、计算机科学、 ...

#21. Shannon Entropy in Configuration Space for Ni-Like ... - MDPI

Discrete Shannon entropy was introduced in view of the mathematical properties of multiconfiguration methods and then used to interpret the information in ...

#22. Shannon Entropy - Statistics How To

Shannon entropy (or just entropy) is a measure of uncertainty (or variability) associated with random variables. It was originally developed ...

#23. What is the role of the logarithm in Shannon's entropy? - Cross ...

Shannon entropy is a quantity satisfying a set of relations. In short, logarithm is to make it growing linearly with system size and "behaving like ...

#24. Shannon Entropy and Fisher Information from a Non-Born ...

We study the Shannon entropy and the Fisher information in a non-Born–Oppenheimer (nBO) regime, where these quantities are constructed from ...

#25. Shannon Entropy - 首頁| Facebook

2020年10月31日週六. Halloween at the Bronze: Buffy the Vampire Slayer VIRTUAL Tribute Event. 34 人有興趣. Shannon Entropy, profile picture ...

#26. shannon-entropy - npm

Shannon Entropy calculation to measure the information gain of an array of objects.

#27. Shannon entropy as a new measure of aromaticity, Shannon ...

Based on the local Shannon entropy concept in information theory, a new measure of aromaticity is introduced. This index, which describes the probability of ...

#28. Shannon entropy of brain functional complex networks under ...

The entropic brain hypothesis holds that the key facts concerning psychedelics are partially explained in terms of increased entropy of the ...

#29. Divergence measures based on the Shannon entropy - IEEE ...

A novel class of information-theoretic divergence measures based on the Shannon entropy is introduced. Unlike the well-known Kullback divergences, ...

#30. A Gentle Introduction to Information Entropy - Machine ...

… the Shannon entropy of a distribution is the expected amount of information in an event drawn from that distribution. It gives a lower bound ...

#31. Infinite Shannon entropy - IOPscience

Even if a probability distribution is properly normalizable, its associated Shannon (or von Neumann) entropy can easily be infinite.

#32. Shannon entropy - The Free Dictionary

Information entropy, also known as Shannon entropy, is proposed by Shannon to solve the problem of quantitative measurement of information. A Security Sandbox ...

#33. What is Shannon Entropy | IGI Global

What is Shannon Entropy? Definition of Shannon Entropy: A measure of the uncertainty in a random variable and quantifies the expected value of the ...

#34. The Shannon Entropy (Short 2012) - IMDb

The Shannon Entropy: Directed by Mackenzie Warner. With Robyn Westcott, Ethan Wright, Ludi Lin, Liam Crawford. When a private video is accidentally uploaded ...

#35. Information entropy (video) | Khan Academy

#36. Shannon entropy for imprecise and under-defined or ...

In this article, it is proposed to extend the using of Shannon entropy to under-defined or over-defined information systems. To be able to use Shannon ...

#37. Shannon entropy calculator — Real example how to calculate ...

Shannon entropy is one of the most important metrics in information theory. Entropy measures the uncertainty associated with a random variable, ...

#38. Shannon Entropy - Bearcave.com

The Shannon entropy equation provides a way to estimate the average minimum number of bits needed to encode a string of symbols, based on the frequency of ...

#39. Shannon Entropy vs. Kolmogorov Complexity | SpringerLink

Most assertions involving Shannon entropy have their Kolmogorov complexity counterparts. A general theorem of Romashchenko [4] states that every information ...

#40. shannon and non-extensive entropy - MATLAB Central

The functions include extensive Shannon and nonextensive Tsallis,escort Tsallis,and renyi entropy. the funcition names start with K_q_ indicate relative ...

#41. 用白話文談數學公式- 熵(entropy)

Claude Shannon 於Information Theory 研究中提出熵(entropy)的概念，可以說是影響後續機器學習(machine learning)發展相當重要的概念。

#42. On Some Shortcomings of Shannon Entropy as a Measure of ...

That is, Shannon entropy of a distribution can be understood as the KL divergence of that distribution relative to a uniform prior distribution ...

#43. Bayesian estimation of shannon entropy - Taylor & Francis ...

Estimation of the Shannon entropy from frequency data is studied. A Bayesian estimator has been proposed using the Dirichlet distribution to ...

#44. Towards an information extraction and knowledge formation ...

Involved method for information quantity estimation is based on Shannon entropy formula. Information and entropy spectrum are decomposed and analysed for ...

#45. Shannon entropy at avoided crossings in the quantum ...

Shannon entropy is studied for the series of avoided crossings that characterize the transition from order to chaos in quantum mechanics.

#46. Shannon entropy double-slit experiment interference fringes

The Shannon entropy has been used to study the localization/delocalization of a distribution for different systems.

#47. Estimation of Entropy, Mutual Information and Related Quantities

This package implements various estimators of the Shannon entropy. ... entropy estimates the Shannon entropy H of the random variable Y from ...

#48. Shannon entropy

Shannon entropy. This chapter is a digression in information theory. This is a fascinating subject, which arose once the notion of information got precise ...

#49. Shannon Entropy Estimation for Linear Processes - EconPapers

By Timothy Fortune and Hailin Sang; Abstract: In this paper, we estimate the Shannon entropy S ( f ) = − E [ log ( f ( x ) ) ] of a ...

#50. Random Words on Entropy and DNS | Splunk

cyber world, lets calculate the Shannon entropy of the domains listed below: The domain aaaaa.com has a Shannon Entropy score of 1.8 (very low) ...

#51. Shannon Entropy - Microsoft Power BI Community

Given a column with a list of values, computes the Shannon Entropy for that set of values. The single measure version of this is: ...

#52. Shannon Entropy versus Renyi Entropy from a Cryptographic ...

mula gives the worst possible amount of collision entropy in a probability distribution, when its Shannon Entropy is fixed. While in practice it is.

#53. Behavioral Implications of Rational Inattention with Shannon ...

... entropy cost functions that better match this feature of the data and that retain key simplifying features of the Shannon model.

#54. Fast Shannon Entropy Calculation - Stack Overflow

Okay, so the answer is that there is no way to do it without calculating the log function, but if you pre-calculate the logs, it's not so bad.

#55. Shannon's entropy | information theory | Britannica

Other articles where Shannon's entropy is discussed: information theory: Entropy: …determines a limit, known as Shannon's entropy, on the best average (that ...

#56. On the Use of Shannon Entropy of the Fission Distribution for ...

On the Use of Shannon Entropy of the Fission Distribution for. Assessing Convergence of Monte Carlo Criticality Calculations. Forrest B. Brown.

#57. Probabilities and Shannon's Entropy in the Everett Many ...

Probabilities and Shannon's Entropy in the Everett Many-Worlds Theory ... Following a controversial suggestion by David Deutsch that decision ...

#58. [PDF] Divergence measures based on the Shannon entropy

A novel class of information-theoretic divergence measures based on the Shannon entropy is introduced, which do not require the condition of absolute ...

#59. Gray Level Image Threshold Using Neutrosophic Shannon Entropy

Gray Level Image Threshold Using Neutrosophic Shannon Entropy Vasile Patrascu, Research Center in Electrical Engineering, Electronics and Information ...

#60. 香农熵理论Shannon Entropy - CSDN博客

Shannon EntropyThe Shannon entropy equation provides a way to estimate the average minimum number of bits needed to encode a string of ...

#61. Shannon Entropy, Information Gain, and Picking Balls from ...

My goal is to understand the concept of entropy, and I always try to ... Shannon Entropy, Information Gain, and Picking Balls from Buckets.

#62. Shannon-entropy Meaning - YourDictionary

What does shannon-entropy mean? Information entropy. (noun) Shannon entropy H is given by the formula where pi is the probability of character number i ...

#63. Characterizations of Shannon and Rényi entropy - Perimeter ...

Shannon entropy. Let p : S → [0,1] is a probability distribution on a finite set S. ▷ Shannon entropy is defined to be. H(p) := −∑ i∈S p(i) log(p(i)).

#64. Shannon Entropy for DNA - Biostars

Shannon's entropy is a quantitative measure of uncertainty in a data set.In most instances it is possible to calculate the entropy scores f… Looking For A ...

#65. Classical Entropy Measures | Quantiki

Classical entropy quantities are a way to quantify how much information is revealed in a random event. Shannon first introduced a way to ...

#66. EntropyExplorer: an R package for computing and comparing ...

Differential Shannon entropy (DSE) and differential coefficient of variation (DCV) are effective metrics for the study of gene expression ...

#67. Shannon entropy | What's new - Terry Tao

Posts about Shannon entropy written by Terence Tao. ... slightly different language of Shannon entropy, and I would like to present it here.

#68. A Mathematical Theory of Communication

A Mathematical Theory of Communication. By C. E. SHANNON ... We shall call H =-∑ pi logpi the entropy of the set of probabilities p1,...,pn. If x is a.

#69. Example of Decision Tree with Shannon Entropy - Zenika

Shannon is an American mathematician. He introduces the idea of entropy to measure disorder in some data. Which one has the highest entropy ...

#70. new method for testing isotropy with Shannon entropy

Abstract. We propose a method for testing isotropy of a three-dimensional distribution using Shannon entropy. We test the method on some Monte Carlo ...

#71. Shannon Entropy - PLANETCALC Online calculators

This online calculator computes Shannon entropy for a given event probability table and for a given message. In information theory, entropy is a measure of ...

#72. Shannon's Experiment to Calculate the Entropy of English

Claude Shannon, the inventor of information theory, devised an experiment aimed at determining the entropy of an English letter (the amount of information ...

#73. On Gibbs-Shannon Entropy - ICTS

The Gibbs-Shannon entropy is Physically consistent, still outside equilibrium. 2. Experimental direct measure of the functional form of. Sbit(p) ...

#74. Shannon entropy in time-varying semantic networks of titles of ...

Despite the growing interest in Shannon entropy, no studies have applied this measure to clique semantic networks.

#75. Shannon Entropy - Methods Blog

The latest Methods in Ecology and Evolution · Tag: Shannon Entropy.

#76. Entropy -- from Wolfram MathWorld

... physical implications as the amount of "disorder" of a system. In mathematics, a more abstract definition is used. The (Shannon) entropy of a variable X ...

#77. Classification of isentropic molecules in terms of Shannon ...

Classification of isentropic molecules in terms of Shannon entropy. Denis Sabirov * and Kamila Koledina. Laboratory of Mathematical Chemistry ...

#78. Properties of Shannon's Entropy - Departamento de ...

Properties of Shannon's Entropy. The measure of uncertainty $ H_n(p_1,p_2,...,p_n)$ given by (1.7) satisfy many interesting properties.

#79. Shannon entropy and the chance meet - LinkedIn

On the 100th birthday of Claude E. Shannon, it is a good occasion to look at the social side of Shannon's information theory and entropy ...

#80. Shannon Entropy Applied to the Measurement of the ...

We investigated the dose-response relation of the Shannon entropy of the electroencephalographic amplitude values during desflurane monoanesthesia in comparison ...

#81. How to calculate Shannon Entropy in Python - Kite

In information theory, Shannon Entropy is an estimation of the average amount of information stored in a random variable. For example, an unbiased coin flip ...

#82. This is IT: A Primer on Shannon's Entropy and Information

Claude [Shannon] didn't like it either. You see, the term 'information theory' suggests that it is a theory about information—but it's not. It's the ...

#83. Calculating Shannon entropy | DAX Cookbook - Packt ...

Shannon entropy, or more generally information entropy, is an important concept in information theory, the field of study that concerns the quantification of ...

#84. Shannon Entropy, Information Gain, and Data Exploration in R

Entropy, as it pertains to information theory, tells us something about the amount of knowledge we have about a given set of things (in this ...

#85. Information entropy - chemeurope.com

In information theory, the Shannon entropy or information entropy is a measure of the uncertainty associated with a random variable.

#86. Tag: Shannon Entropy - BPMSG

As a result the following parameters and diversity indices will be calculated: Richness; Berger-Parker Index; Shannon Entropy (nat); Shannon number equivalent ( ...

#87. Simple Script to Compute Shannon Entropy - One Stop Data ...

This tutorial presents a Python implementation of the Shannon Entropy algorithm to compute Entropy on a DNA/Protein sequence.

#88. Expected Shannon Entropy and Shannon Differentiation ...

In statistics, information theory, ecology, and physics, Shannon entropy has been generalized into numerous parametric families of “generalized ...

#89. Modification of Shannon Entropy to Quantify Mixing in UV ...

In this paper, a modified Shannon entropy mixedness metric was used to quantify mixing in UV reactors. Contrary to the current literature which ...

#90. File:Mplwp shannon entropy.svg - Wikimedia Commons

File:Mplwp shannon entropy.svg. Size of this PNG preview of this SVG file: 600 × 400 pixels. Other resolutions: 320 × 213 pixels | 640 × 427 ...

#91. Shannon entropy - A practical example for map / fold in C++14

In simple terms, Shannon entropy expresses the level of disorganization using probabilities. Look at the examples below. The first pouch has the lowest ...

#92. Shannon's Information Theory | Science4All

The structure of information also lies in the concatenation into longer texts. In fact, Shannon defined the entropy of each character as the ...

#93. shannon entropy - تحلیل آماری

An entropy method is one of the methods based on the existence of information in the decision table. So, in order to solve an issue in an ...

#94. What is Shannon Entropy? - Matthew McGonagle

What is Shannon Entropy? 30 Nov 2017. The purpose of this post is to record some of my musings on Shannon's viewpoint of entropy. This is based on two ...

#95. What is Shannon Information? | Less Than Epsilon

Shannon Entropy of a Coin/Bernoulli Distribution ... Which is plotted below: Entropy of a coin. The entropy is the highest when the coin is fair.

#96. 机器学习入门：重要的概念---信息熵（Shannon's Entropy ...

原创文章，一家之言。 转载请注明出处。 个人公众号：follow_bobo 机器学习入门：重要的概念---信息熵（Shannon's Entropy Model） 在机器学习里面， ...

#97. Episode 71: Shannon Entropy - Podomatic

Shannon Entropy dropped into Mountain Air Studios to talk about craigslist bringing their band together, "guitarmonies", their new record ...