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![PROJECT OVERVIEW Identify the Architecture From the literature survey Model the Architecture into RTL [Register Transfer Level]modeling Verify the functionality of Modeled architecture in MODELSIM® Synthesis the verified design in Xilinx ISE Generation of Bit map file for Dump into Spartan 3E FPGA Program the Bit map file into FPGA. Post simulation in ChipScope pro. 20/06/2011](https://image.slidesharecdn.com/convolutionfinalslides-110717004055-phpapp02/75/Convolution-final-slides-6-2048.jpg)
Convolution final slides
- 1. Presented By :D.Ramu (09605A0401) M.Sirisha (08601A0471) P.Ramya S ree (08601A0497) EFFICIENT FPGA IMPLEMENTATION OF CONVOLUTION Under the Esteemed Guidance of Mr. S.Nagireddy 20/06/2011
- 2. INTRODUCTION Reduces convolutionprocessing time using hardware computing Implements discrete linear convolution of two finite length sequences (N x N) 20/06/2011
- 3. EXISTING SYSTEM Convolutionis implemented using DSP processor Chips Consumes more Power Requires more Chip Area Low Speed 20/06/2011
- 4. PROPOSED SYSTEM Convolutionis implemented using VLSI Architechture Consumes less Power Requires less Chip Area High Speed Extended for Signed and Unsigned Nos. Reduces Processing time 20/06/2011
- 5. PURPOSE Proves thefeasibility of an application specific integrated circuit (ASIC) Digital images can be modified using Point wise operations Image processing operations Provides great significance in discrete signal processing 20/06/2011
- 6. PROJECT OVERVIEW Identifythe Architecture From the literature survey Model the Architecture into RTL [Register Transfer Level]modeling Verify the functionality of Modeled architecture in MODELSIM® Synthesis the verified design in Xilinx ISE Generation of Bit map file for Dump into Spartan 3E FPGA Program the Bit map file into FPGA. Post simulation in ChipScope pro. 20/06/2011
- 7. ADDITIVE PORTION OFLINEAR PROPERTY
- 8. LINEAR CONVOLUTION Impulseresponse Shifted version of the input signal Scaling aspect of linearity of the system Additive aspect of linearity of the system. = y(t)
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- 10. Multiplexer Multiplexerreferred to as “multiplexor” or “mux” MUX contains 2 n Inputs lines n Select lines 1 Output line Working of MUX: Selects any one of the inputs from 2 n inputs Directs to the output depending on n-select lines. 20/06/2011
- 11. Each input is4-bit signed form Each output is also a 4-bit signed form Convolution design uses two 4*1 Multiplexers Multiplexer 4*1 20/06/2011
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- 13. Serial in parallelout block(SIPO) SIPO converts serial input into parallel output Each serial input will be in a 4-bit signed form Working of SIPO Takes SIN(0 to 3) as a input Produces four parallel outputs Q0,Q1,Q2,Q3 Each parallel output will be in a 4-bit signed form 20/06/2011
- 14. Serial In ParallelOut Registers 20/06/2011
- 15. Binary multiplier It is a 4-bit multiplier Takes two four inputs Each input is 4-bit signed form and gives an 8-bit output Special Characteristic of Binary multiplier: Internal carry will not be forwarded to next stage So,number of outputs obtained here is seven only 20/06/2011
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- 18. Register ARegister is a group of flip-flops It holds information within a digital system The logic units get access to the Info during the computing process It may have combinational gates that perform certain data-processing tasks. 20/06/2011
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- 21. 4-INPUT LUT BASEDIMPLEMENTATION OF LOGIC BLOCK
- 22. ADVANTAGES The advantagesof convolution by proposed architecture has following advantages: Reduce area Reduce Power More speed No data loss 20/06/2011
- 23. Simulation Results ConvolutionTop Level 20/06/2011
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- 25. Serial In ParallelOut Registers 20/06/2011
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- 29. Synthesis Results RTLSchematic View 20/06/2011
- 30. RTL Internal View20/06/2011
- 31. APPLICATIONS Digital imageprocessing(Frequency Filtering) Real-time signal processing like: Audio signal processing Video / Image processing Large-capacity data processing In Linear Acoustics In statistics In Probability theory In Optics(The “Blur” is described by Optics) 20/06/2011
- 32. CONCLUSION Optimized implementation of Discrete Linear Convolution. Uses the mean squared error measurement and objective measures of enhancement to achieve a more effective signal processing model and accuracy The proposed circuit uses only 5mw and saves almost 35% area and it takes 20ns to complete. This shows improvement of more than 50% less power. 20/06/2011
- 33. FUTURE SCOPE Extracting a periodic signal from noise. Software Applications: GUI Module. Echo Detection in Linear acoustics. Speech Analysis and pitch. In time-resolved Fluorescense Spectroscopy In Radiotherapy treatment planning systems , most part of all modern codes can use convolution. 20/06/2011
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