Showing posts with label neural networks. Show all posts
Showing posts with label neural networks. Show all posts

Introduction to Digital Signal Processing and Filter Design Review

Introduction to Digital Signal Processing and Filter Design
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Introduction to Digital Signal Processing and Filter Design ReviewThe book is good but the example's are the easy one.Introduction to Digital Signal Processing and Filter Design OverviewA practical and accessible guide to understanding digital signal processingIntroduction to Digital Signal Processing and Filter Design was developed and fine-tuned from the author's twenty-five years of experience teaching classes in digital signal processing. Following a step-by-step approach, students and professionals quickly master the fundamental concepts and applications of discrete-time signals and systems as well as the synthesis of these systems to meet specifications in the time and frequency domains. Striking the right balance between mathematical derivations and theory, the book features:* Discrete-time signals and systems* Linear difference equations* Solutions by recursive algorithms* Convolution* Time and frequency domain analysis* Discrete Fourier series* Design of FIR and IIR filters* Practical methods for hardware implementationA unique feature of this book is a complete chapter on the use of a MATLAB(r) tool, known as the FDA (Filter Design and Analysis) tool, to investigate the effect of finite word length and different formats of quantization, different realization structures, and different methods for filter design. This chapter contains material of practical importance that is not found in many books used in academic courses. It introduces students in digital signal processing to what they need to know to design digital systems using DSP chips currently available from industry.With its unique, classroom-tested approach, Introduction to Digital Signal Processing and Filter Design is the ideal text for students in electrical and electronic engineering, computer science, and applied mathematics, and an accessible introduction or refresher for engineers and scientists in the field.An Instructor's Manual presenting detailed solutions to all the problems in the book is available online from the Wiley editorial department.An Instructor Support FTP site is also available.

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Views into the Chinese Room: New Essays on Searle and Artificial Intelligence Review

Views into the Chinese Room: New Essays on Searle and Artificial Intelligence
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Views into the Chinese Room: New Essays on Searle and Artificial Intelligence ReviewThe Chinese Room Argument (CRA) has nothing to do with the speed of computers or any future developments in artifical intelligence (at least as understood as following from Turing). The CRA is a purely formal argument intended to refute the claim that computers (defined as Turing machines) can think, or can understand, or are minds solely by virtue of their formal description. (This claim is the essence of "computationalism," after Turing's original formulation.) The CRA is that: 1) Syntax is not semantics. 2) The implemented synatactical or formal program of a computer is not sufficient to generate semantics. 3) Minds have semantics. 4) Therefore, computers (so defined) are not minds/cannot think/do not understand because they are not sufficient to generate semantics.
For example, the concepts we employ to think and the words we use to speak have meanings. But there is nothing in computationalism as syntax that has any meaning whatsoever. Whatever meaning an implemented formal program has results from its being programmed or interpreted by us. Syntax (e.g., a computer program) has no causal powers. Whatever causal powers computers have (e.g., to fly airplanes) results from our programming and our assigning interpretations to the electrical charge insides a chip, not from the program in itself.
The chapters in Views Into the Chinese Room attack different aspects of the CRA. But they address it as an argument that stands or falls on the truth of the premises and the validity of the inference, not on engineering questions such as the speed of computers, which are irrelevant. Searle believes that there are, in fact, thinking machines -- we human beings are biological machines that think. And he believes that there also could be artificially made machines that think. The CRA is meant to show only that an implemented computer program by itself cannot generate mental content or semantic content.
For a clear explanation of the CRA, see chapter 15 of this book, by Stevan Harnad, the editor of The Behavioral and Brain Sciences, where Searle's original paper appeared twenty years ago. Do not rely on reviewers who do not understand the argument in the first place.Views into the Chinese Room: New Essays on Searle and Artificial Intelligence OverviewThe most famous challenge to computational cognitive science and artificial intelligence is the philosopher John Searle's "Chinese Room" argument. Searle argued that, although machines can be devised to respond to input with the same output as would a mind, machines--unlike minds--lack understanding of the symbols they process. 19 essays by leading scientists and philosophers assess, renew, and respond to his challenge.

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