The analog neural networks have some very useful advantages in comparison with digital neural network, but recent implementation of discrete elements gives not the possibility for realizing completely these advantages. The reason of this is the great variations of discrete semiconductors characteristics. The VLSI implementation of neural network algorithm is a new direction of analog neural network developments and applications. Analog design can be very difficult because of need to compensate the variations in manufacturing, in temperature, etc. It is necessary to study the characteristics and effectiveness of this implementation. In this article the parameter variation influence over analog neural network behavior has been investigated
