Evolvable Hardware (Genetic and Evolutionary Computation)

Evolvable Hardware (Genetic and Evolutionary Computation)

Xin Yao, Tetsuya Higuchi, Yong Liu

Language: English

Pages: 227

ISBN: 2:00282284

Format: PDF / Kindle (mobi) / ePub


Evolvable hardware (EHW) refers to hardware whose architecture/structure and functions change dynamically and autonomously in order to improve its performance in carrying out tasks. The emergence of this field has been profoundly influenced by the progress in reconfigurable hardware and evolutionary computation. Traditional hardware can be inflexible—the structure and its functions are often impossible to change once it is created. However, most real world problems are not fixed—they change with time. In order to deal with these problems efficiently and effectively, different hardware structures are necessary. EHW provides an ideal approach to make hardware "soft" by adapting the structure to a problem dynamically.

The contributions in this book provide the basics of reconfigurable devices so that readers will be fully prepared to understand what EHW is, why it is necessary and how it is designed. The book also discusses the leading research in digital, analog and mechanical EHW. Selections from leading international researchers offer examples of cutting-edge research and applications, placing particular emphasis on their practical usefulness.

Professionals and students in the field of evolutionary computation will find this a valuable comprehensive resource which provides both the fundamentals and the latest advances in evolvable hardware.

 

 

 

 

 

 

 

 

 

 

 

 

 

experiments for the first time. In these experiments, the parameters for GA operations were specified as follows: • Number of populations: 32 • Crossover rate: 1.0 • Mutation rate: 2/256 Table 3-1 shows pattern classification rates with linear-quantization and with n-LAW quantization. Applying p,-LAW quantization, the pattern classification rate increased by 11.1% (averaged for five subjects) and by 15.5% (maximum; subject 1). Furthermore, the classification rate for the experienced person

worms was combined with more classical anatomical studies obtained by electron microscopy of serial thin sections of the worm at different developmental stages. First, each cell in the adult worm is derived from the "zygote", the first mother cell of the organism, by a virtually invariant series of cell divisions called a "cell lineage". Second, as a direct consequence of the invariant cell lineages, individual nematodes are anatomically invariant carbon copies of each other. The mature adult

architecture of our image-rejection mixer circuit, and detail an adjustment experiment for the image-rejection mixer circuit, which compared the adjustment performances for the GA, a hill-climbing method and manual adjustment. The future work and applications are also discussed in Section 4 before the final summary Section 5. 2. CALIBRATION METHOD USING GENETIC ALGORITHMS FOR ANALOG LSIS In analog LSIs, the characteristics of analog circuits such as resistors and capacitors vary widely due to

creator was installed called Autoit and a macro was written to automate capturing 200 sets of data. Chapter 9 168 Proper technique for testing an ADC involves slightly clipping the input wave. This amounts to several more codes at the boundaries (0 and 16383 in this case) and it allows a more accurate calculation of INL and DNL. In this case a 1.75Vpp covered the full range of the ADC. For each 30°C increment from -180°C to +25°C, 200 files of 16383 samples were acquired. Next, a MATLAB

Heidelberg: dpunkt. Cho, Sung-Bae, Hoai Xuan Nguyen, and Yin Shan (Eds.). 2003. Proceedings of the First Asian-Pacific Workshop on Genetic Programming, vnnr. a s p g p . o r g . Cipriani, Stefano and Anthony A. Takeshian. 2000. Compact cubic function generator. U. S. patent 6,160,427. Filed September 4,1998. Issued December 12,2000. Comisky, William, Jessen Yu, and John Koza. 2000. Automatic synthesis of a wire antenna using genetic programming. Late Breaking Papers at the 2000 Genetic and

Download sample

Download