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An Artificial Neural Network (ANN) system is based on a group of associated units or nodes in a biological brain called neurons. The signal is transferred from one neuron to another neuron. The ANN model accepts the input signal which are multiplied with their weights. The multiplied output is weighted sum with the bias component and processed with the nonlinear signals. In the research work we have considered the 8 inputs ANN signal which are multiplied with their corresponding weights. The hardware chip is designed to support the system functionality in Xilinx ISE 14.2 software. The designed chip is simulated with Modelsim 10.0 software for test cases. The designed chip is also synthesized on SPARTAN-3E FPGA and hardware and timing parameters are also analyzed.
Keywords:
Artificial Neural Network (ANN), FPGA, Xilinx ISE software
Cite Article:
"Artificial Neural Network with Hardware Chip Implementation", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.4, Issue 5, page no.228 - 232, May-2019, Available :http://www.ijrti.org/papers/IJRTI1905053.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator