a fundamental aspect of signal processing is filtering. Filtering involves the manipulation of the spectrum of a signal by passing or blocking certain portions of the spectrum, depending on the frequency of those portions. In this paper, Digital filters are designed using frequency specifications. Matlab provides different options for digital filter design, which includes function, calls to fil...

The common conviction about FIR (finite impulse response) digital filters is that the number of necessary taps, to reach the same performance as provided by IIR (infinite impulse response) digital filters, is usually too large. Moreover, the standard FIR filter design algorithm (Remez exchange) allows the design of linear-phase filters only. Therefore, IIR filters are often preferred over FIR o...

Infinite impulse response filters have not been used extensively in active noise and vibration control applications. The problems are mainly due to the multimodal error surface and instability of adaptive IIR filters used in such applications. Considering these, in this paper a new adaptive recursive RLS-based fast-array IIR filter for active noise and vibration control applications is proposed...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy GLOBAL OPTIMIZATION ALGORITHMS FOR ADAPTIVE INFINITE IMPULSE RESPONSE FILTERS By Ching-An Lai December 2002 Chair: José C. Principe Major Department: Electrical and Computer Engineering The major goal of this dissertation is to develop g...

Design of a digital infinite-impulse-response (IIR) filter is the process of synthesizing and implementing a recursive filter network so that a set of prescribed excitations results a set of desired responses. However, the error surface of IIR filters is usually non-linear and multi-modal. In order to find the global minimum indeed, an improved differential evolution (DE) is proposed for digita...

Infinite impulse response (IIR) systems are widely used in modeling systems such as communications, bio-systems, acoustics, etc. Many algorithms in computational intelligence area have been developed to identify the systems with a novel search technique, but system identification is challenging due to non-unimodality of the error surface and the non-linear relationship between the error signal ...

a fundamental aspect of signal processing is filtering. Filtering involves the manipulation of the spectrum of a signal by passing or blocking certain portions of the spectrum, depending on the frequency of those portions. In this paper, Digital filters are designed using frequency specifications. Matlab provides different options for digital filter design, which includes function, calls to fil...

Insulin-like growth factor-II (IGF-II) is a naturally occurring hormone that exerts neurotrophic and neuroprotective properties in a wide range of neurodegenerative diseases and ageing. Accumulating evidence suggests that the effects of IGF-II in the brain may be explained by its binding to the specific transmembrane receptor, IGFII/M6P receptor (IGF-IIR). However, relatively little is known re...

In this paper, a new family of two-channel low-delay filter banks and wavelet bases using the PR structure in [3] with SOPOT coefficients are proposed. In particular, the functions alpha(z) and beta@) in the structure are chosen as nonlinear-phase FIR and IIR filters, and the design of such multiplier-less filter banks is performed using the genetic algorithm. The proposed design method is very...

In this paper we design a Finite-Impulse-Response (FIR) filter to enforce the so-called Strictly-Positive-Realness (SPR) condition in an adaptive Infinite-Impulse-Response (IIR) filtering context. The paper results may then be used to guarantee the convergence of pseudolinear regression IIR adaptive algorithms.