980 research outputs found

    Design of multidimensional digital filters by spectral transformations

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    Design, stability and applications of two dimensional recursive digital filters

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    Imperial Users onl

    Output Filter Aware Optimization of the Noise Shaping Properties of {\Delta}{\Sigma} Modulators via Semi-Definite Programming

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    The Noise Transfer Function (NTF) of {\Delta}{\Sigma} modulators is typically designed after the features of the input signal. We suggest that in many applications, and notably those involving D/D and D/A conversion or actuation, the NTF should instead be shaped after the properties of the output/reconstruction filter. To this aim, we propose a framework for optimal design based on the Kalman-Yakubovich-Popov (KYP) lemma and semi-definite programming. Some examples illustrate how in practical cases the proposed strategy can outperform more standard approaches.Comment: 14 pages, 18 figures, journal. Code accompanying the paper is available at http://pydsm.googlecode.co

    An Efficient Design of 2-D Digital Filters Using Singular Value Decomposition and Genetic Algorithm with Canonical Signed Digit (CSD) Coefficients

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    In this thesis, the design of 2-D filters by SVD is proposed. This technique reduces the complexity of the designed 2-D digital filters by decomposing it into a set of 1-D digital filters in zl and z2 connected in cascade. The design by SVD can be improved by varying the order of 1-D digital filters in each section based on their corresponding singular values. It is shown that by assigning higher order filters to the sections with greater singular values (SVs), and lower order filters to the sections with lower SVs, a sizable reduction in the total number of required multiplications is achieved. A Genetic Algorithm (GA) is used to design each of the 1-D filters instead of classical optimization. Canonical signed digit system is used to represent filters\u27 coefficients. CSD helps to improve the efficiency of multiplications and thus increase the throughput rate. Examples are provided to demonstrate the effectiveness and usefulness of the proposed technique

    Multimedia applications of three-dimensional digital filters.

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    Digital signal processing has long been an extremely important field of study. One-dimensional and two-dimensional filters have applications in areas such as audio filtering or image processing respectively. As VLSI technology continues to increase, higher-dimensional digital filters are becoming more practical. This thesis investigates the application of Three-Dimensional (3-D) Digital Filters to the area of multimedia. Specifically, it investigates the use of 3-D Interpolation filters to increase the horizontal, vertical, and temporal resolution, or frame rate, of a moving image sequence. The thesis begins by presenting the theory of digital interpolation in one dimension, and then extends that theory to three dimensions. Next the theory is presented for the design of a filter with appropriate characteristics for filtering a video image; i.e. near-linear phase and a steep transition band. After the basic theory is presented, a plan for implementing the filtering of a video image in software is presented along with the relevant file format information. Results from this implementation are shown next, and the thesis ends with a summary and conclusions.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2000 .M34. Source: Masters Abstracts International, Volume: 40-04, page: 1048. Adviser: M. A. Sid-Ahmed. Thesis (M.A.Sc.)--University of Windsor (Canada), 2000

    Digital Filters

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    The new technology advances provide that a great number of system signals can be easily measured with a low cost. The main problem is that usually only a fraction of the signal is useful for different purposes, for example maintenance, DVD-recorders, computers, electric/electronic circuits, econometric, optimization, etc. Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. They can be dynamic, so they can be automatically or manually adjusted to the external and internal conditions. Presented in this book are the most advanced digital filters including different case studies and the most relevant literature

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    http://archive.org/details/geometricdesignt00zumrNAN

    Structures and Algorithms for Two-Dimensional Adaptive Signal Processing

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    Coordinated Science Laboratory was formerly known as Control Systems LaboratoryOpe

    Digital Filter Design Using Improved Teaching-Learning-Based Optimization

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    Digital filters are an important part of digital signal processing systems. Digital filters are divided into finite impulse response (FIR) digital filters and infinite impulse response (IIR) digital filters according to the length of their impulse responses. An FIR digital filter is easier to implement than an IIR digital filter because of its linear phase and stability properties. In terms of the stability of an IIR digital filter, the poles generated in the denominator are subject to stability constraints. In addition, a digital filter can be categorized as one-dimensional or multi-dimensional digital filters according to the dimensions of the signal to be processed. However, for the design of IIR digital filters, traditional design methods have the disadvantages of easy to fall into a local optimum and slow convergence. The Teaching-Learning-Based optimization (TLBO) algorithm has been proven beneficial in a wide range of engineering applications. To this end, this dissertation focusses on using TLBO and its improved algorithms to design five types of digital filters, which include linear phase FIR digital filters, multiobjective general FIR digital filters, multiobjective IIR digital filters, two-dimensional (2-D) linear phase FIR digital filters, and 2-D nonlinear phase FIR digital filters. Among them, linear phase FIR digital filters, 2-D linear phase FIR digital filters, and 2-D nonlinear phase FIR digital filters use single-objective type of TLBO algorithms to optimize; multiobjective general FIR digital filters use multiobjective non-dominated TLBO (MOTLBO) algorithm to optimize; and multiobjective IIR digital filters use MOTLBO with Euclidean distance to optimize. The design results of the five types of filter designs are compared to those obtained by other state-of-the-art design methods. In this dissertation, two major improvements are proposed to enhance the performance of the standard TLBO algorithm. The first improvement is to apply a gradient-based learning to replace the TLBO learner phase to reduce approximation error(s) and CPU time without sacrificing design accuracy for linear phase FIR digital filter design. The second improvement is to incorporate Manhattan distance to simplify the procedure of the multiobjective non-dominated TLBO (MOTLBO) algorithm for general FIR digital filter design. The design results obtained by the two improvements have demonstrated their efficiency and effectiveness
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