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Outline: 1. Introduction 2. Digital processing of continuous-time signals • Retition: Sampling and sampling theorem • Quantization • AD-and DA-conversion 3. DFT and FFT • Leakage effect • Windowing • FFT structure 4. Digital filters • FIR-filters: Structures, linear phase filters, least-squares frequency domain design, Chebyshev approximation • IIR-filters: Structures, classical analog lowpass filter approximations, conversion to digital transfer functions • Finite word-length effects 5. Multirate digital signal processing • Decimation and interpolation • Filters in sampling rate alteration systems • Polyphase decomposition and efficient structures • Digital filter banks Parts of this textbook have been realized in close collaboration with Dr. Joerg Kliewer whom I warmly thank. 6. Spectral estimation • Periodogram, Bartlett's method, Welch's method, Blackman-Tukey method • ARMA modeling, Yule-Walker equation and solution Literature •
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Filtering is a prominent aspect of vast range of signal processing applications like multimedia, communications, biomedical electronics, medical and computer vision, safety and security systems. Today, the core issue of the signal processing is designing a suitable filter for the system. In contrast to analog filters, digital filters are more advantageous as they are characterized by higher stability and precision. The popularity of digital filters is increasing noticeably with the advancement of digital technology. This paper analyzes the design principle of low-pass IIR digital filter by impulse invariance method. MATLAB is a popular numerical analysis software, providing an enormous set of designing tools. A MATLAB-based digital filter design process designs the filter, and mainly analyzes a minimum-order IIR filter, which is designed using Simulink. Through the MATLAB visualization procedures given the frequency characteristics curve, comparing the simulation results. It has the high practical value.
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1998 Annual Conference Proceedings
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CreateSpace Independent Publishing Platform, An Amazon.com Company, ISBN-13 : 978-1514179987
This book is a result of author's thirty-three years of experience in teaching and research in signal processing.The book will guide you from a review of continuous-time signals and systems, through the world of digital signal processing, up to some of the most advanced theory and techniques in adaptive systems, time-frequency analysis, and sparse signal processing. It provides simple examples and explanations for each, including the most complex transform, method, algorithm or approach presented in the book. The most sophisticated results in signal processing theory are illustrated on simple numerical examples. The book is written for students learning digital signal processing and for engineers and researchers refreshing their knowledge in this area. The selected topics are intended for advanced courses and for preparing the reader to solve problems in some of the state of art areas in signal processing.
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This paper considers the constraints imposed on the values of the design parameters in the efficient method proposed by Hedge and Shenoi. We have examined the relationships between the filter parameters in order to make correct specifications of the permissible values of the design parameters.
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In signal processing, a finite impulse response (FIR) filter settles to zero in finite time. FIR filters can be discrete-time or continuous-time, and digital or analog. FIR filter is widely used in various signal processing and image processing applications because of less area, low cost, low power, and high operation speed. An FIR filter is usually implemented by using a series of delays, multipliers, and adders to create the filter's output. We concentrate on the following three categories: frequency sampling methods, windowingbased methods, and optimization-based methods. We also focus on the communications system, including transmissions equipment, relay stations, tributary stations, and other data terminal equipment. A communications system can even include other communications systems.A good example would be a regional emergency response communications system that connects several different cities and allows them to respond to a disaster by integrating systems they have installed for their police and firefighters. In the end,theperformances of severalFIR design methods are assessed. This article provides a comprehensive overview of the latest developments in finite impulse response (FIR) filter design methods in communication systems.
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