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Artificial neural networks (ANNs) are parallel architectures for processing information even though they are usually realized on general-purpose digital computers. This research has been focused on the design, analysis and real-time realization of artificial neural networks using programmable analog hardware for control and classification. We have(More)
With the quick progress of the Human Genome Project, a great amount of uncharacterized DNA sequences needs to be annotated copiously by better algorithms. Recognizing shorter coding sequences of human genes is one of the most important problems in gene recognition, which is not yet completely solved. This paper is devoted to solving the issue using a new(More)
Unmanned ground vehicle (UGV) path-tracking has been an important topic in mechatronics real-time applications. This paper describes and compares the implementation and performance of path-tracking unmanned ground vehicle using a field programmable analog array (FPAA) and conventional digital microcontroller. The FPAA AN10E40 is a general-purpose, digitally(More)
This paper presents a method of realizing artificial neural networks (ANNs) hardware implementation using field programmable analog arrays (FPAAs). A simplified realization for neurons with piecewise linear activation functions is used to reduce the complexity of the neural network architecture. A feedforward neural network is implemented using multi-chip(More)
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