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Digital filter design at gate-level using evolutionary algorithms

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TLDR
It is shown how it is possible to evolve a tiny feed-forward rectangular array of logic gates to perform various filtering tasks – lowpass, bandpass, and multiband.
Abstract
Traditionally digital filters are designed using the concept of a linear difference equation with the output response being a weighted sum of signal samples with usually floating point coefficients Unfortunately such a model is necessarily expensive in terms of hardware as it requires many large bit additions and multiplications In this paper it is shown how it is possible to evolve a tiny feed-forward rectangular array of logic gates to perform various filtering tasks – lowpass, bandpass, and multiband The circuit is evolved by assessing its response to digitised pure sine waves Some of the evolved circuits possess almost linear properties, which means that they are capable of filtering composite signals which have not been encountered in training

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Citations
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Cartesian Genetic Programming

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Evolutionary algorithms with dynamic population size and local exploration for multiobjective optimization

TL;DR: A novel incrementing multiobjective evolutionary algorithm (IMOEA) with dynamic population size that is computed adaptively according to the online discovered tradeoff surface and its desired population distribution density and incorporates the method of fuzzy boundary local perturbation with interactive local fine tuning for broader neighborhood exploration.
Proceedings Article

Acoustic Ranging in Resource-Constrained Sensor Networks.

TL;DR: This paper presents a noise tolerant acoustic ranging mechanism for wireless sensors that employs digital signal processing techniques on standard MICA hardware, and describes how noise canceling, digital filtering and peak detection can be applied to meet the severe resource constraints of the platform.
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Nonlinear blind source separation using higher order statistics and a genetic algorithm

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Cartesian genetic programming

TL;DR: This tutorial will cover the basic technique, advanced developments and applications to a variety of problem domains of Cartesian Genetic Programming, and present a live demo of how the open source cgplibrary can be used.
References
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Book

Digital Signal Processing: A Practical Approach

TL;DR: This book covers a number of DSP techniques that are of particular relevance to industry such as adaptive filtering and multirate processing, and offers modern coverage of the fundamentals, implementation and applications of digital signal processing techniques from a practical point of view.
Journal ArticleDOI

Use of minimum-adder multiplier blocks in FIR digital filters

TL;DR: Three new algorithms for the design of multiplier blocks are described: an efficient modification to an existing algorithm, a new algorithm giving better results, and a hybrid of these two which trades off performance against computation time.
Journal ArticleDOI

A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems

TL;DR: This paper's goals are to present an overview of current-day research, to demonstrate that the POE model can be used to classify bio-inspired systems, and to identify possible directions for future research, derived from a POE outlook.
Book

Genetic programming 1998 : proceedings of the Third Annual Conference, July 22-25, 1998, University of Wisconsin, Madison

John R. Koza
TL;DR: These proceedings present the most recent research in the field of genetic programming as well as recent research results in the fields of genetic algorithms, artificial life and evolution strategies, DNA computing, evolvable hardware, and genetic learning classifier systems.
Book ChapterDOI

Automated Analog Circuit Sythesis Using a Linear Representation

TL;DR: Initial results of the system as applied to two analog filter design problems suggest that the ability to evolve complex analog circuit representations in software is becoming more approachable on a single engineering workstation.
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