M.sc. Mahmoud Kamel, Developing a DSP Core using an FPGA Prototype for Scintillation Detector Signals, supervised by Dr. Ashraf Aboshosha, ICGST

6. Scintillation Detector Figure 1 : Schematic diagram of a scintillation detector

9. Data Acquisition System Figure 2 : The practical data acquisition system of scintillation detector Signals. (1) Scope , (2) high voltage source, (3) scintillator , (4) power supply

12. FPGA Design Flow of the solution Timing Analysis - Verify Performance Specifications Were Met - Static Timing Analysis Gate Level Simulation - Timing Simulation - Verify Design Will Work in Target Technology Program & Test - Program & Test Device on Board t clk

13. Pre-processing Phase 1-Wavelet based Decomposition 2- Interpolation based Reconstruction Pulse Shaping & Counting Multichannel analyzer Store & Show data Figure 3: The overall proposed solution

14. Pre Amplifier Main Amplifier SCA MCA Counter A B Figure 4: The proposed solution

15. Hardware System Figure 5: The FPGA XSC50k-Spartan II and the PC-based parallel interface

17. Effect of Noise on Pulse Shaping & Counting Figure 6: Effect of noise on pulse shaping

19. Wavelet Decomposition Levels H G d 1 X 0 d 2 d 3 Figure 7: Three wavelet decomposition levels A 3 H G

22. Design Block Diagram Figure 8: Design block diagram

24. Decomposition Levels Figure 9: Four approximation coefficients of Haar wavelet transform

25. Statistics of Four Decomposition Levels Table 1: Statistics of four levels Haar transform CC ED MSE PSNR Level 0.9681 20.4778 0.1693 27.8567 One 0.9830 14.7395 0.1575 30.7084 Two 0.9866 12.7990 0.1443 31.9258 Three 0.7021 57.0625 3.2561 18.9554 Four

26. Table 2 : Similarity measure of constructed and original signals of the different mother wavelets Comparison of Different Mother Wavelets CC ED MSE PSNR Mother Wavelet 0.9866 12.7990 0.1643 31.926 Haar 0.9890 11.8139 0.1418 32.5656 Daubechies 0.9900 11.3834 0.1324 32.8635 Coiflet 0.0148 106.878 11.4230 13.5046 Meyer 0.9886 12.2776 0.1533 32.227 Biorthogonal

28. Reconstruct Signals Using Interpolation Figure 10: a) Original signals. b) Transformed signal. c) Reconstructed signals

30. Table 3: Statistics of different interpolation techniques Comparison of Applying Different Interpolation Techniques CC ED MSE PSNR Method 0.9782 16.4669 0.2731 29.7192 Linear 0.9866 12.7990 0.1643 31.9258 Cubic Spline 0.9307 28.8462 0.8380 27.8501 Nearst 0.9818 14.8984 0.2226 30.6066 Cubic Hermit

32. Accumulation Technique Figure 11: Digital processing algorithm of scintillation detector signals

34. Comparison of the Preprocessing Results Table 4: Statistics of the preprocessing techniques CC ED MSE PSNR Method 0.9680 21.3433 0.4555 27.4972 Accumulation Tech 0.9831 14.7856 0.2186 30.6856 Median filter 0.9866 12.7990 0.1643 31.9258 Proposed Solution.

35. Figure 13: Pulse shaping after denoising

36. Figure 14: Pulse counting

38. Multi Channel Analyzer Figure 15: Divided original signals into 16 channels

39. Multi Channel Analyzer Figure 16: Energy spectrum with 16 channels