83:Tb7f,This comprehensive exploration of signals and systems develops continuous- time and discrete-time concepts/methods in parallel highlighting the similarities and differences and features introductory treatments of the applications of these basic methods in such areas as filtering, communication, sampling, discrete-time processing of continuous-time signals, and feedback. Relatively self-contained, the book assumes no prior experience with system analysis, convolution, Fourier analysis, or Laplace and z-transforms.

FEATURES:

Develops continuous-time and discrete-time concepts in parallel highlighting the similarities and differences. E.g.:
- Ch. 1 on basic signals and system properties, Ch. 2 on linear time-invariant systems, and Ch. 3 on Fourier series representation each develop the continuous-time and discrete-time concepts in parallel.
- Ch. 9 on the Laplace Transform and Ch. 10 on the Z-transform deal with the two domains separately, but often draw parallels between results in the two domains.
Introduces some of the important uses of the basic methods that are developed e.g., filtering, communication, sampling, discrete-time processing of continuous-time signals, and feedback.
NEWA companion book contains MATLAB-based computer exercises for each topic.
NEWMaterial on Fourier analysis has been reorganized significantly to provide an easier path for the reader to master and appreciate the importance of this topic. Now represented in four chapters, each of which is far more streamlined and focused, introducing a smaller and more cohesive set of topics.
NEWFrequency-domain filtering is introduced very early in the development to provide a central and concrete illustration of why this topic is important and to provide some intuition with a minimal amount of mathematical preliminaries.
NEWRelocates coverage of Sampling before Communication. * Allows for discussion of important forms of communication, namely those involving discrete or digital signals, in which sampling concepts are intimately involved.
NEWChapter-end Problems
They provide a better balance between exercises developing basic skills and understanding ones that pursue more advanced problem-solving skills. The new edition organizes chapter-end problems into four types of sections which makes it easier for the reader to locate the problems that will best serve their purposes; and provides two types of basic problems, ones with answers (but not solutions); and ones with solutions to provide immediate feedback, while attempting to master the material.
The four types of chapter-end problems are
- Basic Problems with Answers.
- Basic Problems.
- Advanced Problems.
- Extension Problems.

84:T762,For upper-level undergraduate courses in deterministic and stochastic signals and system engineering

An Integrative Approach to Signals, Systems and Inference

Signals, Systems and Inference is a comprehensive text that builds on introductory courses in time- and frequency-domain analysis of signals and systems, and in probability. Directed primarily to upper-level undergraduates and beginning graduate students in engineering and applied science branches, this new textbook pioneers a novel course of study. Instead of the usual leap from broad introductory subjects to highly specialized advanced subjects, this engaging and inclusive text creates a study track for a transitional course. 

Properties and representations of deterministic signals and systems are reviewed and elaborated on, including group delay and the structure and behavior of state-space models. The text also introduces and interprets correlation functions and power spectral densities for describing and processing random signals. Application contexts include pulse amplitude modulation, observer-based feedback control, optimum linear filters for minimum mean-square-error estimation, and matched filtering for signal detection. Model-based approaches to inference are emphasized, in particular for state estimation, signal estimation, and signal detection. 

The text explores ideas, methods and tools common to numerous fields involving signals, systems and inference: signal processing, control, communication, time-series analysis, financial engineering, biomedicine, and many others. Signals, Systems and Inference is a long-awaited and flexible text that can be used for a rigorous course in a broad range of engineering and applied science curricula.

85:T81a,

THE definitive, authoritative book on DSP — ideal for those with an introductory-level knowledge of signals and systems. Written by prominent, DSP pioneers, it provides thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete-time Fourier Analysis. By focusing on the general and universal concepts in discrete-time signal processing, it remains vital and relevant to the new challenges arising in the field — without limiting itself to specific technologies with relatively short life spans.

FEATURES

NEW—Provides a new chapter organization.
NEW—Material on:
- Multi-rate filtering banks.
- The discrete cosine transform.
- Noise-shaping sampling strategies.
NEW—Includes several dozen new problem-solving examples that not only illustrate key points, but demonstrate approaches to typical problems related to the material.
NEW—Contains a wealth of "combat tested" problems which are the best produced over decades of undergraduate and graduate signal processing classes at MIT and Georgia Tech.
NEW—Problems are completely reorganized by level of difficulty into separate categories:
- Basic Problems with Answers to allow the user to check their results, but not solutions (20 per chapter).
- Basic Problems — without answers.
- Advanced Problems.
- Extension Problems — start from the discussion in the book and lead the reader beyond to glimpse some advanced areas of signal processing.
Covers the history of discrete-time signal processing as well as contemporary developments in the field.
Discusses the wide range of present and future applications of the technology.
Focuses on the general and universal concepts in discrete-time signal processing.
Offers a wealth of problems and examples.

86:T475,This is the standard text for introductory advanced undergraduate and first-year graduate level courses in signal processing. The text gives a coherent and exhaustive treatment of discrete-time linear systems, sampling, filtering and filter design, reconstruction, the discrete-time Fourier and z-transforms, Fourier analysis of signals, the fast Fourier transform, and spectral estimation. The author develops the basic theory independently for each of the transform domains and provides illustrative examples throughout to aid the reader. Discussions of applications in the areas of speech processing, consumer electronics, acoustics, radar, geophysical signal processing, and remote sensing help to place the theory in context. The text assumes a background in advanced calculus, including an introduction to complex variables and a basic familiarity with signals and linear systems theory. If you have this background, the book forms an up-to-date and self-contained introduction to discrete-time signal processing that is appropriate for students and researchers. Discrete-Time Signal Processing also includes an extensive bibliography.3c:["$","$L7e",null,{"state":{"mutations":[],"queries":[{"dehydratedAt":1793930590868,"state":{"data":{"pages":[{"requestId":"9296989d-a003-4784-bbf3-6350f30966f2","total":{"value":10,"relation":"eq"},"rows":[{"entityType":"book","isbn":"9781292025902","id":105761,"score":2,"position":0,"book":{"id":105761,"isbn":"9781292025902","created":"2015-12-19T23:00:00.000Z","title":"Signals and systems","description":"For undergraduate-level courses in Signals and Systems.

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