AI Article Synopsis
- The paper presents the design of high-speed second-order infinite impulse response (IIR) notch and anti-notch filters, utilizing a concept called re-timing to enhance speed.
- An innovative detection method for identifying protein hot-spot locations is introduced, which outperforms traditional IIR Chebyshev filter techniques and biological methods.
- The filters are implemented and tested using Xilinx Vivado 18.3 software on a Zynq-7000 Series FPGA, resulting in consistent hot-spot predictions and the discovery of new potential hot-spots.
Article Abstract
In this paper, high-speed second-order infinite impulse response (IIR) notch filter (NF) and anti-notch filter (ANF) are designed and realized on hardware. The improvement in speed of operation for the NF is then achieved by using the re-timing concept. The ANF is designed to specify a stability margin and minimize the amplitude area. Next, an improved approach is proposed for the detection of protein hot-spot locations using the designed second-order IIR ANF. The analytical and experimental results reported in this paper show that the proposed approach provides better hot-spot prediction compared to the reported classical filtering techniques based on the IIR Chebyshev filter and S-transform. The proposed approach also yields consistency in prediction hot-spots compared to the results based on biological methodologies. Furthermore, the presented technique reveals some new "potential" hot-spots. The proposed filters are simulated and synthesized using the Xilinx Vivado 18.3 software platform with Zynq-7000 Series (ZedBoard Zynq Evaluation and Development Kit xc7z020clg484-1) FPGA family.
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| http://dx.doi.org/10.1109/TNB.2023.3238733 | DOI Listing |
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Article Synopsis
- The paper presents the design of high-speed second-order infinite impulse response (IIR) notch and anti-notch filters, utilizing a concept called re-timing to enhance speed.
- An innovative detection method for identifying protein hot-spot locations is introduced, which outperforms traditional IIR Chebyshev filter techniques and biological methods.
- The filters are implemented and tested using Xilinx Vivado 18.3 software on a Zynq-7000 Series FPGA, resulting in consistent hot-spot predictions and the discovery of new potential hot-spots.
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