ANN Architecture for Signal Processing Applications

ANN finds its applications in various signal processing applications such as image recognition(image processing techniques),pattern recognition, system identification, different types of filters(FIR,IIR) and other control problems. In this paper, a multilayer perceptron with more than one hidden layers is considered and for the image processing application such as image recognition, A design of an architecture for multilayer perceptron neuron network is achieved using FPGA. The design is implemented by using the different activation functions such as linear activation function, hard limiter activation function, piecewise linear activation function etc.. A neural network was implemented by using VHDL hardware description Language codes and XC3S250E-PQ 208 Xilinx FPGA device. The results were presented using Xilinx Foundation 9.2i. Index terms Multilayer Perceptron, Back propagation, Activation functions, FPGA, Neuron Plan approximation. ——————————  ——————————