www.xilinx.com 1 © 2009 Xilinx, Inc. All rights reserved. XILINX, the Xilinx logo, and other designated brands included herein are trademarks of Xilinx, Inc. All other trademarks are the property of their respective owners. A large percentage of filters implemented in the digital domain are Finite Impulse Response (FIR) filters. These filters are used over a wide range of sample rates and are w...

For recursive filter2 the maximal sample frequency is bounded by the recursive loops in the filter. In this work, a filter structure based on the use of the frequency masking approach is presented that increases the maximal sample frequency for narrowband and wideband filters by introducing more delay elements in the recursive loops. By using identical subfilters (except for the periods), the s...

A part of low level image processing consists of the detection (by filtering) of sharp level variations of luminance in the image to obtain the edge segments, extremities and angles. To select the geometrical information related to the structure of the objects present in an image, a key step consists of extracting the edges of the considered objects. Several accurate numerical algorithms have b...

This paper develops a new design scheme for the phase response of an all-pass recursive digital filter. A variant of particle swarm optimization (PSO) algorithm will be utilized for solving this kind of filter design problem. It is here called the modified PSO (MPSO) algorithm in which another adjusting factor is more introduced in the velocity updating formula of the algorithm in order to impr...

Optimal digital data detection for a linear Gaussian (fading) channel is considered in the context of the estimator-correlator and recent recursive structures for sequence detection. It is noted that the complexity of the “estimator” (i.e., prediction filter) and “correlator” (i.e., sequence search) can be varied independently. This concept is demonstrated for flat

In this paper, a robust statistics based filter to remove salt and pepper noise in digital images is presented. The function of the algorithm is to detect the corrupted pixels first since the impulse noise only affect certain pixels in the image and the remaining pixels are uncorrupted. The corrupted pixels are replaced by an estimated value using the proposed robust statistics based filter. Th...

The incorporation of the neural architectures in adaptive filtering applications has been addressed in detail. In particular, the Underdetermined-Order Recursive Least-Squares (URLS) algorithm, which lies between the wellknown Normalized Least Mean Square and Recursive Least Squares algorithms, is reformulated via a neural architecture. The response of the neural network is seen to be identical...

[2] S. Nishimura, K. Hirano, and R. N. Pal, “A new class of very low sensitivity and low roundoff noise recursive digital filter structures,” IEEE Trans. Circui& Sysf., vol. CAS-28, pp. 1152-1158, Dec. 1981. [3] A. Sedlmeyer and A. Fettweis, “Digital filters with true ladder configuration,” Int. J. Circuit Theory Appl., vol. 1, pp. 5-10, 1913. [4] L. T. Bruton, “Low-sensitivity digital ladder f...