Content-Addressable Memories

Springer Series in Information Sciences

Book 1
Springer Science & Business Media
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Designers and users of computer systems have long been aware of the fact that inclusion of some kind of content-addressable or "associative" functions in the storage and retrieval mechanisms would allow a more effective and straightforward organization of data than with the usual addressed memories, with the result that the computing power would be significantly increased. However, although the basic principles of content-addressing have been known for over twenty years, the hardware content-addressable memories (CAMs) have found their way only to special roles such as small buffer memories and con trol units. This situation now seems to be changing: Because of the develop ment of new technologies such as very-large-scale integration of semiconduc tor circuits, charge-coupled devices, magnetic-bubble memories, and certain devices based on quantum-mechanical effects, an increasing amount of active searching functions can be transferred to memory units. The prices of the more complex memory components which earlier were too high to allow the application of these principles to mass memories will be reduced to a fraction of the to tal system costs, and this will certainly have a significant impact on the new computer architectures. In order to advance the new memory principles and technologies, more in formation ought to be made accessible to a common user.
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Publisher
Springer Science & Business Media
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Published on
Dec 6, 2012
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Pages
368
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ISBN
9783642965524
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Language
English
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Genres
Computers / Intelligence (AI) & Semantics
Computers / Software Development & Engineering / General
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This content is DRM protected.
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Due to continual progress in the large-scale integration of semiconductor circuits, parallel computing principles can already be met in low-cost sys tems: numerous examples exist in image processing, for which special hard ware is implementable with quite modest resources even by nonprofessional designers. Principles of content addressing, if thoroughly understood, can thereby be applied effectively using standard components. On the other hand, mass storage based on associative principles still exists only in the long term plans of computer technologists. This situation is somewhat confused by the fact that certain expectations are held for the development of new storage media such as optical memories and "spin glasses" (metal alloys with low-density magnetic impurities). Their technologies, however, may not ripen until after "fifth generation" computers have been built. It seems that software methods for content addressing, especially those based on hash coding principles, are still holding their position firmly, and a few innovations have been developed recently. As they need no special hardware, one might expect that they will spread to a wide circle of users. This monograph is based on an extensive literature survey, most of which was published in the First Edition. I have added Chap. ?, which contains a review of more recent work. This updated book now has references to over 1200 original publications. In the editing of the new material, I received valuable help from Anneli HeimbUrger, M. Sc. , and Mrs. Leila Koivisto.
In the first edition of this book, we covered in Chapter 6 and 7 the applications to multidimensional convolutions and DFT's of the transforms which we have introduced, back in 1977, and called polynomial transforms. Since the publication of the first edition of this book, several important new developments concerning the polynomial transforms have taken place, and we have included, in this edition, a discussion of the relationship between DFT and convolution polynomial transform algorithms. This material is covered in Appendix A, along with a presentation of new convolution polynomial transform algorithms and with the application of polynomial transforms to the computation of multidimensional cosine transforms. We have found that the short convolution and polynomial product algorithms of Chap. 3 have been used extensively. This prompted us to include, in this edition, several new one-dimensional and two-dimensional polynomial product algorithms which are listed in Appendix B. Since our book is being used as part of several graduate-level courses taught at various universities, we have added, to this edition, a set of problems which cover Chaps. 2 to 8. Some of these problems serve also to illustrate some research work on DFT and convolution algorithms. I am indebted to Mrs A. Schlageter who prepared the manuscript of this second edition. Lausanne HENRI J. NUSSBAUMER April 1982 Preface to the First Edition This book presents in a unified way the various fast algorithms that are used for the implementation of digital filters and the evaluation of discrete Fourier transforms.
Pitch (i.e., fundamental frequency FO and fundamental period TO) occupies a key position in the acoustic speech signal. The prosodic information of an utterance is predominantly determined by this parameter. The ear is more sensitive to changes of fundamental frequency than to changes of other speech signal parameters by an order of magnitude. The quality of vocoded speech is essentially influenced by the quality and faultlessness of the pitch measure ment. Hence the importance of this parameter necessitates using good and reliable measurement methods. At first glance the task looks simple: one just has to detect the funda mental frequency or period of a quasi-periodic signal. For a number of reasons, however, the task of pitch determination has to be counted among the most difficult problems in speech analysis. 1) In principle, speech is a nonstationary process; the momentary position of the vocal tract may change abruptly at any time. This leads to drastic variations in the temporal structure of the signal, even between subsequent pitch periods, and assuming a quasi-periodic signal is often far from realistic. 2) Due to the flexibility of the human vocal tract and the wide variety of voices, there exist a multitude of possible temporal structures. Narrow-band formants at low harmonics (especially at the second or third harmonic) are an additional source of difficulty. 3) For an arbitrary speech signal uttered by an unknown speaker, the fundamental frequency can vary over a range of almost four octaves (50 to 800 Hz).
A. L. Macintosh, Napier University, UK The papers in this volume are the refereed application papers presented at ES2004, the Twenty-fourth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2004. The conference was organised by SGAI, the British Computer Society Specialist Group on Artificial Intelligence. This volume contains twenty refereed papers which present the innovative application of a range of AI techniques in a number of subject domains. This year, the papers are divided into sections on Synthesis and Prediction, Scheduling and Search, Diagnosis and Monitoring, Classification and Design, and Analysis and Evaluation This year's prize for the best refereed application paper, which is being sponsored by the Department of Trade and Industry, was won by a paper entitled "A Case-Based Technique for Tracking Concept Drift in Spam Filtering". The authors are Sarah Jane Delany, from the Dublin Institute of Technology, Ireland, and Padraig Cunningham, Alexey Tsymbal, and Lorcan Coyle from Trinity College Dublin, Ireland. This is the twelfth volume in the Applications and Innovations series. The Technical Stream papers are published as a companion volume under the title Research and Development in Intelligent Systems XXI. On behalf of the conference organising committee I should like to thank all those who contributed to the organisation of this year's application programme, in particular the programme committee members, the executive programme committee and our administrators Linsay Turbert and Collette Jackson.
In the first edition of this book, we covered in Chapter 6 and 7 the applications to multidimensional convolutions and DFT's of the transforms which we have introduced, back in 1977, and called polynomial transforms. Since the publication of the first edition of this book, several important new developments concerning the polynomial transforms have taken place, and we have included, in this edition, a discussion of the relationship between DFT and convolution polynomial transform algorithms. This material is covered in Appendix A, along with a presentation of new convolution polynomial transform algorithms and with the application of polynomial transforms to the computation of multidimensional cosine transforms. We have found that the short convolution and polynomial product algorithms of Chap. 3 have been used extensively. This prompted us to include, in this edition, several new one-dimensional and two-dimensional polynomial product algorithms which are listed in Appendix B. Since our book is being used as part of several graduate-level courses taught at various universities, we have added, to this edition, a set of problems which cover Chaps. 2 to 8. Some of these problems serve also to illustrate some research work on DFT and convolution algorithms. I am indebted to Mrs A. Schlageter who prepared the manuscript of this second edition. Lausanne HENRI J. NUSSBAUMER April 1982 Preface to the First Edition This book presents in a unified way the various fast algorithms that are used for the implementation of digital filters and the evaluation of discrete Fourier transforms.
The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains. If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of our species then would come to depend on the actions of the machine superintelligence. But we have one advantage: we get to make the first move. Will it be possible to construct a seed AI or otherwise to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation? To get closer to an answer to this question, we must make our way through a fascinating landscape of topics and considerations. Read the book and learn about oracles, genies, singletons; about boxing methods, tripwires, and mind crime; about humanity's cosmic endowment and differential technological development; indirect normativity, instrumental convergence, whole brain emulation and technology couplings; Malthusian economics and dystopian evolution; artificial intelligence, and biological cognitive enhancement, and collective intelligence. This profoundly ambitious and original book picks its way carefully through a vast tract of forbiddingly difficult intellectual terrain. Yet the writing is so lucid that it somehow makes it all seem easy. After an utterly engrossing journey that takes us to the frontiers of thinking about the human condition and the future of intelligent life, we find in Nick Bostrom's work nothing less than a reconceptualization of the essential task of our time.
Pitch (i.e., fundamental frequency FO and fundamental period TO) occupies a key position in the acoustic speech signal. The prosodic information of an utterance is predominantly determined by this parameter. The ear is more sensitive to changes of fundamental frequency than to changes of other speech signal parameters by an order of magnitude. The quality of vocoded speech is essentially influenced by the quality and faultlessness of the pitch measure ment. Hence the importance of this parameter necessitates using good and reliable measurement methods. At first glance the task looks simple: one just has to detect the funda mental frequency or period of a quasi-periodic signal. For a number of reasons, however, the task of pitch determination has to be counted among the most difficult problems in speech analysis. 1) In principle, speech is a nonstationary process; the momentary position of the vocal tract may change abruptly at any time. This leads to drastic variations in the temporal structure of the signal, even between subsequent pitch periods, and assuming a quasi-periodic signal is often far from realistic. 2) Due to the flexibility of the human vocal tract and the wide variety of voices, there exist a multitude of possible temporal structures. Narrow-band formants at low harmonics (especially at the second or third harmonic) are an additional source of difficulty. 3) For an arbitrary speech signal uttered by an unknown speaker, the fundamental frequency can vary over a range of almost four octaves (50 to 800 Hz).
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