Telecommunications Sensors

Download Introduction to Evolvable Hardware: A Practical Guide for by Garrison W. Greenwood PDF

Posted On April 11, 2017 at 1:14 pm by / Comments Off on Download Introduction to Evolvable Hardware: A Practical Guide for by Garrison W. Greenwood PDF

By Garrison W. Greenwood

Creation to Evolvable undefined: a pragmatic advisor for Designing Self-Adaptive structures presents a primary advent for engineers, designers, and bosses taken with the advance of adaptive, excessive reliability structures. It additionally introduces the thoughts of evolvable (EHW) to new researchers in a based manner. With this useful ebook, it is easy to quick practice the ideas offered to current layout difficulties.

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Extra info for Introduction to Evolvable Hardware: A Practical Guide for Designing Self-Adaptive Systems

Sample text

The initial population is a set of randomly generated computer programs that are usually represented as rooted, point-labeled trees with ordered branches. Each tree is mapped to a labeled cyclic graph that represents a physical circuit. Reproduction is performed with random mutation and crossover operators. 32 FUNDAMENTALS OF EVOLUTIONARY COMPUTATION The execution time for a genetic programming algorithm used to solve an EHW problem can last for days—even though the algorithm is usually running on a large multiprocessor system.

At that time the 74 series and the 4000 series standard digital gates were used for random glue logic (random looking logic structure, usually used to interface different parts of a system). But for commercial systems the requirement was for an application specific integrated circuit (ASIC) that could be easily manufactured to perform a specific function. Unfortunately the manufacturing time for the design and implementation of a complete chip was (and still is) prohibitively expensive for Introduction to Evolvable Hardware: A Practical Guide for Designing Self-Adaptive Systems, by Garrison W.

The objective function doesn’t really provide much help. Unfortunately, in some problems maximizing a desirable property may also maximize an undesirable property. For instance, circuits that operate at high speed also tend to have high power consumption. Obviously a high value should be awarded for correct operation at a high speed, but if low power consumption is also necessary, somehow this information should appear in the objective function’s format. Put another way, if solution s and s both operate correctly and at the same speed, but s consumes less power, then we want O(s) > O(s ).

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