Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

Digital filters can be broadly classified into two groups: recursive (infinite impulse response (IIR)) and non-recursive (finite impulse response (FIR)). An IIR filter can provide a much better performance than the FIR filter having the same number of coefficients. However, IIR filters might have a multi-modal error surface. Therefore, a reliable design method proposed for IIR filters must be based on a global search procedure. Artificial bee colony (ABC) algorithm has been recently introduced for global optimization. The ABC algorithm simulating the intelligent foraging behaviour of honey bee swarm is a simple, robust, and very flexible algorithm. In this work, a new method based on ABC algorithm for designing digital IIR filters is described and its performance is compared with that of a conventional optimization algorithm (LSQ-nonlin) and particle swarm optimization (PSO) algorithm.

/pdf/a-new-design-method-based-on-artificial-bee-colony-algorithm-4h83c1feyi.pdf

A new design method based on artificial bee colony algorithm for digital IIR filters

Brief paper: H∞ filtering for 2D Markovian jump systems

digital signal processing a computer based approach is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the digital signal processing a computer based approach is universally compatible with any devices to read.

Digital Signal Processing A Computer Based Approach

We present a unified approach to the design of two well-known classes of computationally efficient digital filters, namely the interpolated and frequency-response-masking (FRM) FIR filters, that are optimized in minimax sense. The highly nonconvex minimax designs of these filters are carried out by jointly optimizing the subfilters involved using a convex-concave procedure (CCP) that yields an iterative and converging process where each iteration involves a convex problem of minimizing a linear function subject to convex quadratic constraints. We present an analysis to explain why CCP is well-suited for the design problems at hand. We also show that the CCP-based design framework is flexible to allow extension to the design of FRM filters that simultaneously promotes sparsity of the filter coefficients to reduce implementation complexity. Design examples with comparisons are presented to demonstrate the performance of the proposed design methods.

A Unified Approach to the Design of Interpolated and Frequency-Response-Masking FIR Filters

Orthogonal frequency division multiple access (OFDMA) allows multiple users to make use of the same bandwidth as the single-user OFDM for data transmission and is a promising candidate to be used for future cellular systems. A key issue at hand is the rate-adaptive resource allocation problem. In this paper, we propose two subcarrier allocation schemes with low complexities based on the magnitude of the channel frequency responses. The proposed methods ensure a fair resource allocation in terms of the number of subcarriers with affordable bit-rates. Monte-Carlo simulations show that our proposed methods achieve a higher overall bit-rate for all users compared to previously derived subcarrier allocation schemes

Subcarrier Allocation for multi-user OFDM system

This paper treats the coefficient sensitivity of two-dimensional (2-D) separable-denominator digital filters using the Roesser local state-space model. Two techniques suitable for 2-D separable-denominator digital filters are developed for synthesizing the filter structure with low sensitivity, one free from 12 scaling constraints on the state variables, and the other under the scaling constraints. In the paper, it is clarified that the filter structures with low sensitivity can be easily derived from the balanced realization. Finally, an example is given to illustrate the utility of the proposed techniques.

Synthesis of 2-D separable-denominator digital filters with low sensitivity

We present a unified approach to minimax design of interpolated and frequency-response-masking FIR filters which are well-known classes of computationally efficient digital filter. The highly nonconvex minimax designs of these filters are carried out by jointly optimizing the subfilters involved using a convex-concave procedure (CCP). We explain why CCP is well-suited for the design problems at hand and present two design instances to demonstrate its performance.

A unified approach to the design of interpolated and frequency-response-masking FIR filters

Roundoff noise (RN) is known to exist in digital filters and systems under finite-precision operations and can become a critical factor for severe performance degradation in infinite impulse response (IIR) filters and systems. In the literature, two classes of methods are available for RN reduction or minimization-one uses state-space coordinate transformation, the other uses error feedback/feed-forward of state variables. In this paper, we propose a method for the joint optimization of error feedback/feed-forward and state-space realization. It is shown that the problem at hand can be solved in an unconstrained optimization setting. With a closed-form formula for gradient evaluation and an efficient quasi-Newton solver, the unconstrained minimization problem can be solved efficiently. With the infinite-precision solution as a reference point, we then move on to derive a semidefinite programming (SDP) relaxation method for an approximate solution of optimal error-feedback matrix with sum-of-power-of-two entries under a given state-space realization. Simulations are presented to illustrate the proposed algorithms and demonstrate the performance of optimized systems.

/pdf/jointly-optimized-error-feedback-and-realization-for-1rnry2o92j.pdf

Takao Hinamoto

Papers

A Unified Approach to the Design of Interpolated and Frequency-Response-Masking FIR Filters

Subcarrier Allocation for multi-user OFDM system

Synthesis of 2-D separable-denominator digital filters with low sensitivity

A unified approach to the design of interpolated and frequency-response-masking FIR filters

Jointly optimized error-feedback and realization for roundoff noise minimization in state-space digital filters