利用遗传算法实现可进化硬件的功能级

B. Karunya, R. Uma
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引用次数: 7

摘要

实时过滤数据需要专用的硬件来满足苛刻的时间要求。信号处理的一个重要特征是处理噪声。为了能够在大范围的输入信号和噪声中实现所需的输出信号,希望能够调整滤波器特性和滤波器类型。这样得到的滤波器被称为自适应滤波器。我们提出了一种采用片上可进化硬件方法来进化自适应数字滤波器的片上解决方案。这个项目是关于使用遗传算法实现可进化的硬件。它正式介绍了可进化硬件,这是一种新的硬件范式,其中硬件建立在可重构器件(如pld和fpga)上,其架构可以通过使用遗传算法等进化计算技术重新配置,以适应新环境
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Functional Level Implementation Of Evolvable Hardware Using Genetic Algorithms
Filtering data in real time requires dedicated hardware to meet demanding time requirements. One important feature of signal processing is coping with noise. To be able to achieve the required output signal for a wide range of input signals and noise, it is desirable to be able to adjust both the filter characteristics and the type of filter. In this way the resulting filter is said to be an adaptive filter. We propose an on-chip solution for evolving an adaptive digital filter using an on-chip evolvable hardware method. This project is about implementing evolvable hardware using genetic algorithms. It gives a formal introduction to evolvable hardware, which is a new hardware paradigm in which hardware is built on reconfigurable devices such as PLDs and FPGAs whose architectures can be reconfigured by using evolutionary computation techniques such as genetic algorithms, to adapt to the new environment
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