Microelectronics Engineering

Permanent URI for this collection

http://etd.aau.edu.et/handle/12345678/194

Browse

Browsing Microelectronics Engineering by Subject "electronic"

Now showing 1 - 1 of 1
  • No Thumbnail Available
    Item
    Investigation of Soft Neural Network Algorithm Implement to Analog Electronics Devices
    (Addis Ababa University, 2018-12-31) Eyob, Gedlie; Getachew, Alemu (PhD)
    The implementation of neural systems is presented in this paper. The thesis focuses on implementations where the algorithms and their physical support are tightly coupled. This thesis describes a neural network intelligent, application, soft-algorithm to implement to hardware electronics device. With the emerging of Integrated Circuit, any design with large number of electronic components can be squeezed into a tiny chip area with minimum power requirements, which leads to integration of innumerable applications so as to design any electronic consumer product initiated in the era of digital convergence. One has many choices for selecting either of these reconfigurable techniques based on Speed, Gate Density, Development, Prototyping, simulation time and cost. This thesis describes the implementation in hardware of an Artificial Neural Network with an Electronic circuit made up of Op-amps. The implementation of a Neural Network in hardware can be desired to benefit from its distributed processing capacity or to avoid using a personal computer attached to each implementation. The hardware implementation is based in a Feed Forward Neural Network, with a hyperbolic tangent as activation function, with floating point notation of single precision. The device used was an electronic circuit made with Op-amps The Proteus Software version 8.0 was used to validate the implementation results of the hardware circuit. The results show that the implementation does not introduce a noticeable loss of precision but is slower than the software implementation running in a PC.