ビッグデータ信号処理のための低遅延・低演算駆動FIRフィルタの制約付き最適化

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タイトル別名
  • A Constraint Optimization of Low-delay and Low-operation Driven FIR Digital Filters for Big Data Signal Processing
  • ビッグデータ シンゴウ ショリ ノ タメ ノ テイチエン ・ テイエンザン クドウ FIR フィルタ ノ セイヤク ツキ サイテキカ
  • A constraint optimization of low‐delay and low‐operation driven FIR digital filters for big data signal processing

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<p>In big data signal processing system, low-delay and low-operation driven digital filters are required for large amounts of data processing. We introduce a design method for low-delay FIR (finite impulse response) filters with semi-sparse coefficients. The semi-sparse coefficients stand for to have some 0 ± values with real values. The semi-sparse coefficients leads to reduction of number of multipliers. We show the design problem of the filters are formulated in a constraint optimization problem. Also, we propose a design algorithm to solve the design problem. Using the filters, the number of multipliers can be reduced. Finally, we present examples to demonstrate the effectiveness of the proposed method.</p>

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