Claude Shannon and the Making of Information Theory
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Bernard M. Oliver Oral History Interview
http://oac.cdlib.org/findaid/ark:/13030/kt658038wn Online items available Bernard M. Oliver Oral History Interview Daniel Hartwig Stanford University. Libraries.Department of Special Collections and University Archives Stanford, California November 2010 Copyright © 2015 The Board of Trustees of the Leland Stanford Junior University. All rights reserved. Note This encoded finding aid is compliant with Stanford EAD Best Practice Guidelines, Version 1.0. Bernard M. Oliver Oral History SCM0111 1 Interview Overview Call Number: SCM0111 Creator: Oliver, Bernard M., 1916- Title: Bernard M. Oliver oral history interview Dates: 1985-1986 Physical Description: 0.02 Linear feet (1 folder) Summary: Transcript of an interview conducted by Arthur L. Norberg covering Oliver's early life, his education, and work experiences at Bell Laboratories and Hewlett-Packard. Subjects include television research, radar, information theory, organizational climate and objectives at both companies, Hewlett-Packard's associations with Stanford University, and Oliver's association with William Hewlett and David Packard. Language(s): The materials are in English. Repository: Department of Special Collections and University Archives Green Library 557 Escondido Mall Stanford, CA 94305-6064 Email: [email protected] Phone: (650) 725-1022 URL: http://library.stanford.edu/spc Information about Access Reproduction is prohibited. Ownership & Copyright All requests to reproduce, publish, quote from, or otherwise use collection materials must be submitted in writing to the Head of Special Collections and University Archives, Stanford University Libraries, Stanford, California 94304-6064. Consent is given on behalf of Special Collections as the owner of the physical items and is not intended to include or imply permission from the copyright owner. -
Terms for Talking About Information and Communication
Information 2012, 3, 351-371; doi:10.3390/info3030351 OPEN ACCESS information ISSN 2078-2489 www.mdpi.com/journal/information Concept Paper Terms for Talking about Information and Communication Corey Anton School of Communications, Grand Valley State University, 210 Lake Superior Hall, Allendale, MI 49401, USA; E-Mail: [email protected]; Tel.: +1-616-331-3668; Fax: +1-616-331-2700 Received: 4 June 2012; in revised form: 17 August 2012 / Accepted: 20 August 2012 / Published: 27 August 2012 Abstract: This paper offers terms for talking about information and how it relates to both matter-energy and communication, by: (1) Identifying three different levels of signs: Index, based in contiguity, icon, based in similarity, and symbol, based in convention; (2) examining three kinds of coding: Analogic differences, which deal with positive quantities having contiguous and continuous values, and digital distinctions, which include “either/or functions”, discrete values, and capacities for negation, decontextualization, and abstract concept-transfer, and finally, iconic coding, which incorporates both analogic differences and digital distinctions; and (3) differentiating between “information theoretic” orientations (which deal with data, what is “given as meaningful” according to selections and combinations within “contexts of choice”) and “communication theoretic” ones (which deal with capta, what is “taken as meaningful” according to various “choices of context”). Finally, a brief envoi reflects on how information broadly construed relates to probability and entropy. Keywords: sign; index; icon; symbol; coding; context; information; communication “If you have an apple and I have an apple and we exchange apples then you and I will still each have one apple. -
2008 Annual Report
2008 Annual Report NATIONAL ACADEMY OF ENGINEERING ENGINEERING THE FUTURE 1 Letter from the President 3 In Service to the Nation 3 Mission Statement 4 Program Reports 4 Engineering Education 4 Center for the Advancement of Scholarship on Engineering Education 6 Technological Literacy 6 Public Understanding of Engineering Developing Effective Messages Media Relations Public Relations Grand Challenges for Engineering 8 Center for Engineering, Ethics, and Society 9 Diversity in the Engineering Workforce Engineer Girl! Website Engineer Your Life Project Engineering Equity Extension Service 10 Frontiers of Engineering Armstrong Endowment for Young Engineers-Gilbreth Lectures 12 Engineering and Health Care 14 Technology and Peace Building 14 Technology for a Quieter America 15 America’s Energy Future 16 Terrorism and the Electric Power-Delivery System 16 U.S.-China Cooperation on Electricity from Renewables 17 U.S.-China Symposium on Science and Technology Strategic Policy 17 Offshoring of Engineering 18 Gathering Storm Still Frames the Policy Debate 20 2008 NAE Awards Recipients 22 2008 New Members and Foreign Associates 24 2008 NAE Anniversary Members 28 2008 Private Contributions 28 Einstein Society 28 Heritage Society 29 Golden Bridge Society 29 Catalyst Society 30 Rosette Society 30 Challenge Society 30 Charter Society 31 Other Individual Donors 34 The Presidents’ Circle 34 Corporations, Foundations, and Other Organizations 35 National Academy of Engineering Fund Financial Report 37 Report of Independent Certified Public Accountants 41 Notes to Financial Statements 53 Officers 53 Councillors 54 Staff 54 NAE Publications Letter from the President Engineering is critical to meeting the fundamental challenges facing the U.S. economy in the 21st century. -
Harry Nyquist 1889-1976
Nyquist and His Seminal Papers Harry Nyquist 1889-1976 Karl Johan Åström A Gifted Scientist and Department of Mechanical Engineering Engineer University of California Santa Barbara Johnson-Nyquist noise The Nyquist frequency Nyquist’s Stability Criterion ASME Nyquist Lecture 2005 ASME Nyquist Lecture 2005 Introduction 1.Introduction 2.A Remarkable Career • Thank you for honoring Nyquist • Thank you for inviting me to give this lecture 3.Communications • Nyquist was awarded the Rufus Oldenburger 4.Johnson-Nyquist Noise medal in 1975 5.Stability Theory • The person and his contributions • What we can learn 6.Summary ASME Nyquist Lecture 2005 ASME Nyquist Lecture 2005 A Remarkable Career Born in Nilsby Sweden February 7 1889 6 years in school Emigrated to USA 1907 Farmhand Teachers College University of North Dakota PhD Physics Yale University 1917 AT&T Bell Labs 1917-1954 Consultant 1954-1965 ASME Nyquist Lecture 2005 ASME Nyquist Lecture 2005 Becoming a Teacher is my Dream Rubrik • Emigrated 1907 • Southern Minnesota Normal College, Austin Active as in teaching • Back to SMNC • Exam 1911 valedictarian • High School Teacher 1912 ASME Nyquist Lecture 2005 ASME Nyquist Lecture 2005 A Dream Comes True Academia Pulls University of North Dakota BS EE 1914 MS EE 1915 Very active in student organizations met Johnson Yale University PhD Physics 1917. Thesis topic: On the Stark effect in Helium and Neon. Largely experimental. ASME Nyquist Lecture 2005 ASME Nyquist Lecture 2005 The ATT Early Fax A Career in AT&T Bell commersial from 1925 • 1917 AT&T Engineering Department • 1919 Department of Development and Research • 1935 Bell Labs • World War II • 1952 Assistant director fo Systems Studies • 1954 Retired • 1954-1962 Consulting ASME Nyquist Lecture 2005 ASME Nyquist Lecture 2005 An Unusual Research Lab In His Right Environment Control the telephone monoply • Nyquist thrived, challenging problems, clever Key technologies collegues, interesting. -
By Dean R. Johnson
Alice Symposium 2009 Duke University “Who needs PowerPoint? I’ve got Alice!” By Dean R. Johnson I. Background of My Experience in Programming II. Experience with Alice A. Changes in Languages and Student Population B. Introducing Alice C. Enrollment Data III. History Lesson: Significant People in Computing A. Paper B. PowerPoint C. Alice 1. Lesson Plan 2. Grading Rubric IV. Sample Projects: Screenshots and descriptions of Student Work I. Background I started my study of Computer Science in 1982 as a high school senior when I enrolled in a one semester course titled “Computer Programming.” It was taught by my math teacher and at first seemed like a very mystifying idea. We wrote programs in BASIC b y “bubbling in” punch cards. After completing the program, we took the stack of cards to the back of the room handing them to our teacher. He was the only one allowed to insert the cards into the card reader. The PDP-11 interpreted our program and if it ran successfully, the dot matrix printer printed a table of the whole numbers from one to ten and their squares. It was amazing. The strange thing about this description is that it brings back such fond memories for me. It was during this brief exposure to programming that I was hooked for life. This is what drives me on a daily basis to do the best I can to expose students to the fascinating world of programming. I graduated from UW-Whitewater in 1986 with a Major in Mathematics and a Minor in Computer Science. -
Claude Elwood Shannon (1916–2001) Solomon W
Claude Elwood Shannon (1916–2001) Solomon W. Golomb, Elwyn Berlekamp, Thomas M. Cover, Robert G. Gallager, James L. Massey, and Andrew J. Viterbi Solomon W. Golomb Done in complete isolation from the community of population geneticists, this work went unpublished While his incredibly inventive mind enriched until it appeared in 1993 in Shannon’s Collected many fields, Claude Shannon’s enduring fame will Papers [5], by which time its results were known surely rest on his 1948 work “A mathematical independently and genetics had become a very theory of communication” [7] and the ongoing rev- different subject. After his Ph.D. thesis Shannon olution in information technology it engendered. wrote nothing further about genetics, and he Shannon, born April 30, 1916, in Petoskey, Michi- expressed skepticism about attempts to expand gan, obtained bachelor’s degrees in both mathe- the domain of information theory beyond the matics and electrical engineering at the University communications area for which he created it. of Michigan in 1936. He then went to M.I.T., and Starting in 1938 Shannon worked at M.I.T. with after spending the summer of 1937 at Bell Tele- Vannevar Bush’s “differential analyzer”, the an- phone Laboratories, he wrote one of the greatest cestral analog computer. After another summer master’s theses ever, published in 1938 as “A sym- (1940) at Bell Labs, he spent the academic year bolic analysis of relay and switching circuits” [8], 1940–41 working under the famous mathemati- in which he showed that the symbolic logic of cian Hermann Weyl at the Institute for Advanced George Boole’s nineteenth century Laws of Thought Study in Princeton, where he also began thinking provided the perfect mathematical model for about recasting communications on a proper switching theory (and indeed for the subsequent mathematical foundation. -
Digital Communication Systems 2.2 Optimal Source Coding
Digital Communication Systems EES 452 Asst. Prof. Dr. Prapun Suksompong [email protected] 2. Source Coding 2.2 Optimal Source Coding: Huffman Coding: Origin, Recipe, MATLAB Implementation 1 Examples of Prefix Codes Nonsingular Fixed-Length Code Shannon–Fano code Huffman Code 2 Prof. Robert Fano (1917-2016) Shannon Award (1976 ) Shannon–Fano Code Proposed in Shannon’s “A Mathematical Theory of Communication” in 1948 The method was attributed to Fano, who later published it as a technical report. Fano, R.M. (1949). “The transmission of information”. Technical Report No. 65. Cambridge (Mass.), USA: Research Laboratory of Electronics at MIT. Should not be confused with Shannon coding, the coding method used to prove Shannon's noiseless coding theorem, or with Shannon–Fano–Elias coding (also known as Elias coding), the precursor to arithmetic coding. 3 Claude E. Shannon Award Claude E. Shannon (1972) Elwyn R. Berlekamp (1993) Sergio Verdu (2007) David S. Slepian (1974) Aaron D. Wyner (1994) Robert M. Gray (2008) Robert M. Fano (1976) G. David Forney, Jr. (1995) Jorma Rissanen (2009) Peter Elias (1977) Imre Csiszár (1996) Te Sun Han (2010) Mark S. Pinsker (1978) Jacob Ziv (1997) Shlomo Shamai (Shitz) (2011) Jacob Wolfowitz (1979) Neil J. A. Sloane (1998) Abbas El Gamal (2012) W. Wesley Peterson (1981) Tadao Kasami (1999) Katalin Marton (2013) Irving S. Reed (1982) Thomas Kailath (2000) János Körner (2014) Robert G. Gallager (1983) Jack KeilWolf (2001) Arthur Robert Calderbank (2015) Solomon W. Golomb (1985) Toby Berger (2002) Alexander S. Holevo (2016) William L. Root (1986) Lloyd R. Welch (2003) David Tse (2017) James L. -
Marconi Society - Wikipedia
9/23/2019 Marconi Society - Wikipedia Marconi Society The Guglielmo Marconi International Fellowship Foundation, briefly called Marconi Foundation and currently known as The Marconi Society, was established by Gioia Marconi Braga in 1974[1] to commemorate the centennial of the birth (April 24, 1874) of her father Guglielmo Marconi. The Marconi International Fellowship Council was established to honor significant contributions in science and technology, awarding the Marconi Prize and an annual $100,000 grant to a living scientist who has made advances in communication technology that benefits mankind. The Marconi Fellows are Sir Eric A. Ash (1984), Paul Baran (1991), Sir Tim Berners-Lee (2002), Claude Berrou (2005), Sergey Brin (2004), Francesco Carassa (1983), Vinton G. Cerf (1998), Andrew Chraplyvy (2009), Colin Cherry (1978), John Cioffi (2006), Arthur C. Clarke (1982), Martin Cooper (2013), Whitfield Diffie (2000), Federico Faggin (1988), James Flanagan (1992), David Forney, Jr. (1997), Robert G. Gallager (2003), Robert N. Hall (1989), Izuo Hayashi (1993), Martin Hellman (2000), Hiroshi Inose (1976), Irwin M. Jacobs (2011), Robert E. Kahn (1994) Sir Charles Kao (1985), James R. Killian (1975), Leonard Kleinrock (1986), Herwig Kogelnik (2001), Robert W. Lucky (1987), James L. Massey (1999), Robert Metcalfe (2003), Lawrence Page (2004), Yash Pal (1980), Seymour Papert (1981), Arogyaswami Paulraj (2014), David N. Payne (2008), John R. Pierce (1979), Ronald L. Rivest (2007), Arthur L. Schawlow (1977), Allan Snyder (2001), Robert Tkach (2009), Gottfried Ungerboeck (1996), Andrew Viterbi (1990), Jack Keil Wolf (2011), Jacob Ziv (1995). In 2015, the prize went to Peter T. Kirstein for bringing the internet to Europe. Since 2008, Marconi has also issued the Paul Baran Marconi Society Young Scholar Awards. -
Toward a New Science of Information
Data Science Journal, Volume 6, Supplement, 7 April 2007 TOWARD A NEW SCIENCE OF INFORMATION D Doucette1*, R Bichler 2, W Hofkirchner2, and C Raffl2 *1 The Science of Information Institute, 1737 Q Street, N.W. Washington, D.C. 20009, USA Email: [email protected] 2 ICT&S Center, University of Salzburg - Center for Advanced Studies and Research in Information and Communication Technologies & Society, Sigmund-Haffner-Gasse 18, 5020 Salzburg, Austria Email: [email protected], [email protected], [email protected] ABSTRACT The concept of information has become a crucial topic in several emerging scientific disciplines, as well as in organizations, in companies and in everyday life. Hence it is legitimate to speak of the so-called information society; but a scientific understanding of the Information Age has not had time to develop. Following this evolution we face the need of a new transdisciplinary understanding of information, encompassing many academic disciplines and new fields of interest. Therefore a Science of Information is required. The goal of this paper is to discuss the aims, the scope, and the tools of a Science of Information. Furthermore we describe the new Science of Information Institute (SOII), which will be established as an international and transdisciplinary organization that takes into consideration a larger perspective of information. Keywords: Information, Science of Information, Information Society, Transdisciplinarity, Science of Information Institute (SOII), Foundations of Information Science (FIS) 1 INTRODUCTION Information is emerging as a new and large prospective area of study. The notion of information has become a crucial topic in several emerging scientific disciplines such as Philosophy of Information, Quantum Information, Bioinformatics and Biosemiotics, Theory of Mind, Systems Theory, Internet Research, and many more. -
4 Classical Error Correcting Codes
“Machines should work. People should think.” Richard Hamming. 4 Classical Error Correcting Codes Coding theory is an application of information theory critical for reliable communication and fault-tolerant information storage and processing; indeed, Shannon channel coding theorem tells us that we can transmit information on a noisy channel with an arbitrarily low probability of error. A code is designed based on a well-defined set of specifications and protects the information only for the type and number of errors prescribed in its design. Agoodcode: (i) Adds a minimum amount of redundancy to the original message. (ii) Efficient encoding and decoding schemes for the code exist; this means that information is easily mapped to and extracted from a codeword. Reliable communication and fault-tolerant computing are intimately related to each other; the concept of a communication channel, an abstraction for a physical system used to transmit information from one place to another and/or from one time to another is at the core of communication, as well as, information storage and processing. It should however be clear 355 Basic Concepts Linear Codes Polynomial Codes Basic Concepts Linear Codes Other Codes Figure 96: The organization of Chapter 4 at a glance. that the existence of error-correcting codes does not guarantee that logic operations can be implemented using noisy gates and circuits. The strategies to build reliable computing systems using unreliable components are based on John von Neumann’s studies of error detection and error correction techniques for information storage and processing. This chapter covers topics from the theory of classical error detection and error correction and introduces concepts useful for understanding quantum error correction, the subject of Chapter 5. -
Information Theory and the Length Distribution of All Discrete Systems
Information Theory and the Length Distribution of all Discrete Systems Les Hatton1* Gregory Warr2** 1 Faculty of Science, Engineering and Computing, Kingston University, London, UK 2 Medical University of South Carolina, Charleston, South Carolina, USA. * [email protected] ** [email protected] Revision: $Revision: 1.35 $ Date: $Date: 2017/09/06 07:30:43 $ Abstract We begin with the extraordinary observation that the length distribution of 80 million proteins in UniProt, the Universal Protein Resource, measured in amino acids, is qualitatively identical to the length distribution of large collections of computer functions measured in programming language tokens, at all scales. That two such disparate discrete systems share important structural properties suggests that yet other apparently unrelated discrete systems might share the same properties, and certainly invites an explanation. We demonstrate that this is inevitable for all discrete systems of components built from tokens or symbols. Departing from existing work by embedding the Conservation of Hartley-Shannon information (CoHSI) in a classical statistical mechanics framework, we identify two kinds of discrete system, heterogeneous and homogeneous. Heterogeneous systems contain components built from a unique alphabet of tokens and yield an implicit CoHSI distribution with a sharp unimodal peak asymptoting to a power-law. Homogeneous systems contain components each built from arXiv:1709.01712v1 [q-bio.OT] 6 Sep 2017 just one kind of token unique to that component and yield a CoHSI distribution corresponding to Zipf’s law. This theory is applied to heterogeneous systems, (proteome, computer software, music); homogeneous systems (language texts, abundance of the elements); and to systems in which both heterogeneous and homogeneous behaviour co-exist (word frequencies and word length frequencies in language texts). -
Chapter 4 Information Theory
Chapter Information Theory Intro duction This lecture covers entropy joint entropy mutual information and minimum descrip tion length See the texts by Cover and Mackay for a more comprehensive treatment Measures of Information Information on a computer is represented by binary bit strings Decimal numb ers can b e represented using the following enco ding The p osition of the binary digit 3 2 1 0 Bit Bit Bit Bit Decimal Table Binary encoding indicates its decimal equivalent such that if there are N bits the ith bit represents N i the decimal numb er Bit is referred to as the most signicant bit and bit N as the least signicant bit To enco de M dierent messages requires log M bits 2 Signal Pro cessing Course WD Penny April Entropy The table b elow shows the probability of o ccurrence px to two decimal places of i selected letters x in the English alphab et These statistics were taken from Mackays i b o ok on Information Theory The table also shows the information content of a x px hx i i i a e j q t z Table Probability and Information content of letters letter hx log i px i which is a measure of surprise if we had to guess what a randomly chosen letter of the English alphab et was going to b e wed say it was an A E T or other frequently o ccuring letter If it turned out to b e a Z wed b e surprised The letter E is so common that it is unusual to nd a sentence without one An exception is the page novel Gadsby by Ernest Vincent Wright in which