Efficient FPGA based architecture for high‐order FIR filtering using simultaneous DSP and LUT reduced utilization
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Bibliographic record
Abstract
Abstract This paper proposes an efficient high‐order finite impulse response (FIR) filter structure for field programmable gate array (FPGA)‐based applications with simultaneous digital signal processing (DSP) and look‐up‐table (LUT) reduced utilization. The real‐time updating of the filter coefficients is also put into perspective. In order to perform these objectives, both the speed and the structure of FPGA are efficiently exploited. The gap between the required input sampling frequency and the FPGA allowed maximum frequency is managed to achieve additional computing sequences. Furthermore, the special structures of the FPGA Look‐up‐table Shift‐Register (LUT‐SR) and their internal connections are fully employed for pipelining and selecting the input samples. The FPGA Block RAMs (BRAMs) are employed for handling the reconfigurable filter coefficients, and the FPGA DSP slices are associated for computing the output data of the BRAMs and the multiplexers. To synchronize the BRAM unit addressing with the LUT multiplexer selection, a single unit is used for simultaneous control. The obtained results show that the proposed reconfigurable 16‐tap FIR filter offers reductions of 79.3% and 74.4% of slice utilization over the hybrid variable size partitioning (VP‐Hybrid) based structure and the Radix‐2 r based structure, respectively when implemented on a Xilinx Spartan‐6 XC6SLX45 FPGA. Moreover, an improvement of efficiency is achieved compared to all reputed FPGA‐based architectures.
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Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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