Multiplier is playing asignificant role in a wide range of applications including like embedded systems, VLSI, and digital signal processing. Computation is significant in image processing. In image processing, various problems occur in neural networks.Computational is to solve the problem.The processing of computation is power consumption, design complexity, andreduces the error.The fuzzy neural network optimization approximates multiplier using the nonlinear anisotropic diffusion image denoisingmethod.The noise image from the input images is removed using nonlinear anisotropic diffusion image denoising.The fuzzy neural network optimization of an approximate multiplieris used to minimize the design complexity and increase the speed.The FNNOAM-NLADID method implements the neural network system to remove the noisy image and develop the design on a multiplier basis. This method is utilized to design the ideal components: adder, tree, and compressor. A neural network system is an essential part of our body. The FNNAOM-NLADID method performs power consumption, peak signal-to-noise ratio, error and noise; these factors are considered in the design.Digital signal processing in real time to computational building block, arithmetic and logic unit, and accumulator.This method, FNNOAM-NLADID based on the decreased design complexity and power consumption to achieve the technique.Neural networks simplify the mathematics of complex input and output and reduce the multiplicative noise.

Fuzzy neural network, denoising, noise, multiplier, power consumption