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Signal Processing and Machine Learning Theory, authored by world-leading experts, reviews the principles, methods and techniques of essential and advanced signal processing theory. These theories and tools are the driving engines of many current and emerging research topics and technologies, such as machine learning, autonomous vehicles, the internet of things, future wireless communications, medical imaging, etc. Provides quick tutorial reviews of important and emerging topics of research in signal processing-based tools Presents core principles in signal processing theory and shows their applications Discusses some emerging signal processing tools applied in machine learning methods References content on core principles, technologies, algorithms and applications Includes references to journal articles and other literature on which to build further, more specific, and detailed knowledge
This first volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory. With this reference source you will: Quickly grasp a new area of research Understand the underlying principles of a topic and its application Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved Quick tutorial reviews of important and emerging topics of research in machine learning Presents core principles in signal processing theory and shows their applications Reference content on core principles, technologies, algorithms and applications Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic
129 6.2 Representation of hints. 131 6.3 Monotonicity hints .. . 134 6.4 Theory ......... . 139 6.4.1 Capacity results 140 6.4.2 Decision boundaries 144 6.5 Conclusion 145 6.6 References....... ... 146 7 Analysis and Synthesis Tools for Robust SPRness 147 C. Mosquera, J.R. Hernandez, F. Perez-Gonzalez 7.1 Introduction.............. 147 7.2 SPR Analysis of Uncertain Systems. 153 7.2.1 The Poly topic Case . 155 7.2.2 The ZP-Ball Case ...... . 157 7.2.3 The Roots Space Case ... . 159 7.3 Synthesis of LTI Filters for Robust SPR Problems 161 7.3.1 Algebraic Design for Two Plants ..... . 161 7.3.2 Algebraic Design for Three or More Plants 164 7.3.3 Approximate Design Methods. 165 7.4 Experimental results 167 7.5 Conclusions 168 7.6 References ..... . 169 8 Boundary Methods for Distribution Analysis 173 J.L. Sancho et aZ. 8.1 Introduction ............. . 173 8.1.1 Building a Classifier System . 175 8.2 Motivation ............. . 176 8.3 Boundary Methods as Feature-Set Evaluation 177 8.3.1 Results ................ . 179 8.3.2 Feature Set Evaluation using Boundary Methods: S- mary. . . . . . . . . . . . . . . . . . . .. . . 182 . . .
This practical guide helps readers to learn how to develop and implement synchronization functions in digital communication systems.
"This book covers basic and the advanced approaches in the design and implementation of multirate filtering"--Provided by publisher.
Designed for senior electrical engineering students, this textbook explores the theoretical concepts of digital signal processing and communication systems by presenting laboratory experiments using real-time DSP hardware. The experiments are designed for the Texas Instruments TMS320C6701 Evaluation Module or TMS320C6711 DSK but can easily be adapted to other DSP boards. Each chapter begins with a presentation of the required theory and concludes with instructions for performing experiments to implement the theory. In the process of performing the experiments, students gain experience in working with software tools and equipment commonly used in industry.