Design of FIR filters for low implementation complexity

The minimisation of the total number of power-of-two terms is considered. The number of terms per coefficient is not constrained. Arbitrary phase filters are also designed where a method is introduced for the optimal utilisation of the filter gain. The method produces much better results than other methods in the literature with low computational requirements

Design of linear phase FIR digital filters with discrete valued coefficients

Ph.D. - Doctoral Progra

New initialization methods for discrete coefficient FIR filter design with coefficient scaling and the use of scale factor in the design process

The initialization of filter coefficients in discrete-coefficient finite-impulse-response (FIR) filter design (with coefficient scaling) using coefficient-value-assignment-based optimization techniques is considered. A common weakness of existing initialization measures, a total-square-error (TSE) measure and a maximum-error (ME) measure, is described. New TSE and ME measures that overcome the weakness are introduced. As opposed to the current knowledge, it is revealed that TSE and ME measures do not necessarily provide different initial coefficient set information and that the initial coefficient set information by the ME measure is not unique in general. On a parallel track, the treatment of coefficient scaling in the optimization process is considered. The closed-form expression of the objective function normalized peak ripple magnitude (NPRM), which was defined implicitly in the literature, is given. In contrast to existing methods, the computation of NPRM accordingly does not require a scale-factor parameter independent of filter coefficients although coefficient scaling persists. Then, TSE and ME measures become practically equivalent (although, in general, they indicate different initial scale factors) since an explicit scale factor parameter is no longer needed

An efficient local search method guided by gradient information for discrete coefficient FIR filter design

A new local search method for the design of linear phase FIR filters with discrete valued coefficients is introduced in this paper. Conventional minimax criterion and normalized peak ripple magnitude (NPRM) are taken as objective functions. The principle is to search along low gradient routes with priority and to direct the search toward steeper sides as improved solutions cease to appear. The characteristics of the objective functions have been explained and used to devise the method. The method is novel in the way it generates the gradient information and makes use of it. At each step, a number of filter coefficients are picked according to the gradient information and perturbed to look for improved solutions. A specific neighborhood definition is proposed and used in perturbing the coefficients. The method has very low computational demand and is suitable for the design of long filters. The results of design examples demonstrate that the performance of the method can compete with those of optimal methods. Along the way, a closed form expression for the "filter gain" that minimizes NPRM is also given. Furthermore, it is shown that a previously proposed local search method unintentionally implements the ideas of this paper in an opposite order

Normalized peak rippple magnitude as an objective function in discrete coefficient fir filter design

Normalized peak ripple magnitude (NPRM) has been a convenient design criterion for discrete coefficient FIR filters. "Filter gain" is the major concern for NPRM. This paper presents an exact closed form expression of the filter gain for a given set of filter coefficients. Based on this expression the characteristics of NPRM cost function are discussed. The selection of the initial value of the filter gain for suboptimal design methods is considered. Deficiency of the previously proposed methods is pointed out and a way to overcome the problem is presented. Proposed solution provides additional information that has been proved to be useful in determining the initial point when using a suboptimal optimization method

Design of FIR filters with arbitrary magnitude and phase responses and powers-of-two coefficients

The design of FIR filters with minimal implementation complexity is considered. A method is proposed for the minimization of the total number of power-of-two terms when the magnitude and phase responses are to be specifed arbitrarly. The solution to find the optimal filter gain for these type of filters (non linear-phase) is given

Gradient controlled improved proportionate affine projection sign algorithm

Recently, proportionate adaptive filters are commonly used in the acoustic echo cancellation problems. In proportionate adaptive filters, for each coefficient a step-size which proportional to magnitude of that coefficient is applied. Hence, adaptive filter converges more rapidly to its steady state. Developed proportionate method were applied to algorithms which are robust against impulsive noise. Consequently, algorithms which converge quickly and robust against impulsive noise are obtained for acoustic channels. In this paper, we proposed Gradient Controlled Improved Proportionate Affine Projection Sign Algorithm, which is obtained by modifying Gradient Controlled Improved Proportionate Affine Projection Algorithm such that it will work for acoustic channel with impulsive noise. According to the simulation results, proposed algorithm has better performance than the algorithms in the literature in terms of convergence speed

The use of articulator motion information in automatic speech segmentation

The use of articulator motion information in automatic speech segmentation is investigated. Automatic speech segmentation is an essential task in speech processing applications like speech synthesis where accuracy and consistency of segmentation are firmly connected to the quality of synthetic speech. The motions of upper and lower lips are incorporated into a hidden Markov model based segmentation process. The MOCHA-TIMIT database, which involves simultaneous articulatograph and microphone recordings, was used to develop and test the models. Different feature vector compositions are proposed for incorporation of articulator motion parameters to the automatic segmentation system. Average absolute boundary error of the system with respect to manual segmentation is decreased by 10.1%. The results are examined in a boundary class dependent manner using both acoustic and visual phone classes, and the performance of the system in different boundary types is discussed. After analyzing the boundary class dependent performance, the error reduction is increased to 18.0% by using the appropriate feature vectors in selected boundaries

Automatic Segmentation of High Speed Video Images of Vocal Folds

An automatic method for segmenting glottis in high speed endoscopic video (HSV) images of vocal folds is proposed. The method is based on image histogram modeling. Three fundamental problems in automatic histogram based processing of HSV images, which are automatic localization of vocal folds, deformation of the intensity distribution by nonuniform illumination, and ambiguous segmentation when glottal gap is small, are addressed. The problems are solved by using novel masking, illumination, and reflectance modeling methods. The overall algorithm has three stages: masking, illumination modeling, and segmentation. Firstly, a mask is determined based on total variation norm for the region of interest in HSV images. Secondly, a planar illumination model is estimated from consecutive HSV images and reflectance image is obtained. Reflectance images of the masked HSV are used to form a vertical slice image whose reflectance distribution is modeled by a Gaussian mixture model (GMM). Finally, estimated GMM is used to isolate the glottis from the background. Results show that proposed method provides about 94% improvements with respect to manually segmented data in contrast to conventional method which uses Rayleigh intensity distribution in extracting the glottal areas