Signals and systems primer with MATLAB
著者
書誌事項
Signals and systems primer with MATLAB
（The electrical engineering and applied signal processing series）
CRC Press, c2007
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注記
Includes index
内容説明・目次
内容説明
Signals and Systems Primer with MATLAB (R) equally emphasizes the fundamentals of both analog and digital signals and systems. To ensure insight into the basic concepts and methods, the text presents a variety of examples that illustrate a wide range of applications, from microelectromechanical to worldwide communication systems. It also provides MATLAB functions and procedures for practice and verification of these concepts.
Taking a pedagogical approach, the author builds a solid foundation in signal processing as well as analog and digital systems. The book first introduces orthogonal signals, linear and time-invariant continuous-time systems, discrete-type systems, periodic signals represented by Fourier series, Gibbs's phenomenon, and the sampling theorem. After chapters on various transforms, the book discusses analog filter design, both finite and infinite impulse response digital filters, and the fundamentals of random digital signal processing, including the nonparametric spectral estimation. The final chapter presents different types of filtering and their uses for random digital signal processing, specifically, the use of Wiener filtering and least mean squares filtering.
Balancing the study of signals with system modeling and interactions, this text will help readers accurately develop mathematical representations of systems.
目次
Signals and Their Functional Representation. Linear Continuous-Time Systems. Discrete Systems. Periodic Continuous Signals and Their Spectrums. Nonperiodic Signals and Their Fourier Transform. Sampling of Continuous Signals. Discrete-Time Transforms. Laplace Transform. The Z-Transform, Difference Equations, and Discrete Systems. Analog Filter Design. Finite Impulse Response (FIR) Filters. Infinite Impulse Response (IIR) Filters. Random Variables, Sequences, and Power Spectra Densities. Least Square System Design, Wiener Filter, and the LMS Filter. Appendices.
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