1. Presenting: Itai Avron Supervisor: Chen Koren Characterization Presentation Spring 2005 Implementation of Artificial Intelligence System on FPGA

2. Project Goals Creating a VHDL design of a Neural Network Comparison Vs. software implementation (Matlab) If the time will suffice: Implementing Learning Algorithm (BP)

3. Background Neural Network is a Learning Machine It is build from Neurons (Perceptrons), which holds the knowledge of the system within their inter-connection strength Every Neuron Implement the Active Function:

4. System Interface Input: - Image (16x16 pixels) - Weights Output: - A number between 0-9 (4 bit vector)

5. System Architecture control SRAM (Xilinx) Neuron Input Output …

6. Neuron Architecture Multipliers for calculating (Xilinx) SRAM implementing Activation Function SRAM saving W and X

7. Controller – Flow Diagram Idle Upload Image and Weights Calculate Hidden Layer Calculate Exit Layer New Image Until all Neurons are calculated Upload Input to Neuron Neuron Calculation Save Neuron Result

8. Schedule 7.6-14.6: Planning the Controller, Block Diagram 14.6-21.6: Implementing the NN in Matlab 21.6-5.7: Implementing a single Neuron 5.7-19.7: Implementing the controller End of July: Midterm Presentation 19.7-26.7: Implementing the NN 26.7-9.8: Debugging and Simulating the NN September: Final Presentation