Yutana Jewajinda

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This paper presents a cellular compact genetic algorithm (CCGA) for evolvable and adaptive hardware. The CCGA has cellular-like structure which is suitable for hardware implementation. The CCGA is developed from compact genetic algorithm (CGA) and parallel estimation of distribution algorithm (EDA). The concept and algorithm of the CCGA are presented. The(More)
This paper presents a parallel genetic algorithm (GA) called the cellular compact genetic algorithm (c-cGA) and its implementation for adaptive hardware. An adaptive hardware based on the c-cGA is proposed to automate real-time classification of ECG signals. The c-cGA not only provides a strong search capability while maintaining genetic diversity using(More)
This paper presents a cellular compact genetic algorithm (CCGA) for evolvable hardware. The CCGA has cellular-like structure which is suitable for hardware implementation. The CCGA is developed from cooperative compact genetic algorithm (CoCGA). The concept and algorithm of the CCGA are presented. The standard test functions are selected to measure the(More)
This paper presents FPGA-based ECG signal classification based-on a parallel genetic algorithm and block-based neural network. The proposed parallel genetic algorithm has cellular-like structure which is suitable for hardware implementation. With online learning using hardware parallel genetic algorithm to block-based neural network, the complete ECG signal(More)
This paper presents a hardware implementation of evolvable block-based neural network (BBNN) amd a kind of EDAs called cellular compact genetic algorithm (CCGA) in FPGA. The CCGA and BBNN have cellular-like and array-like structures which are suitable for hardware implementation. The implemented hardware demonstrates the completely intrinsic online(More)
  • Y. Jewajinda
  • 2008
This paper presents an adaptive/evolvable hardware architecture and its FPGA implementation. The adaptive hardware is based-on evolvable block-based neural network (BBNN) and a cellular compact genetic algorithm (CCGA). The BBNN consists of a 2-D array of modular neuron. The CCGA has a cellular-like structure. A proposed layer-based architecture provides a(More)
This paper presents a parallel probabilistic model-building genetic algorithms (PMBGAs) called cellular compact genetic algorithm (CCGA) with elitism. The elitism-based CCCA is a coarse-grained parallel GA that migrates probability model between nodes instead of individuals. Each CCGA node is enhanced from compact genetic algorithm by using elitism. With(More)
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