A Constraint Optimization of Low-delay and Low-operation Driven FIR Digital Filters for Big Data Signal Processing
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- Hirakawa Tomohiro
- Graduate School of Engineering, Hiroshima University
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- Nakamoto Masayoshi
- Graduate School of Engineering, Hiroshima University
Bibliographic Information
- Other Title
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- 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
- 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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Description
<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>
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 138 (4), 299-305, 2018
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390001204612285696
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- NII Article ID
- 130006602466
- 210000169482
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 19429541
- 03854221
- 19429533
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- NDL BIB ID
- 028996952
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- OpenAIRE
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- Abstract License Flag
- Disallowed