• 제목/요약/키워드: 아날로그 셀룰라 병렬처리 회로망

검색결과 2건 처리시간 0.018초

아날로그 2차원 셀의 순환형 배열을 이용한 R=l/2. K=7형 고속 비터비 디코더 설계 (Design of R=1/2, K=7 Type High Speed Viterbi Decoder with Circularly Connected 2-D Analog Parallel Processing Cell Array)

  • 손홍락;김형석
    • 대한전기학회논문지:시스템및제어부문D
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    • 제52권11호
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    • pp.650-656
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    • 2003
  • A high speed Viterbi decoder with a circularly connected 2-dimensional analog processing ceil array Is proposed. The proposed Viterbi .decoder has a 2-dimensional parallel processing structure in which an analog processing cell is placed at each node of a trellis diagram, the output column of the analog processing cells is connected to the decoding column, and thus, the output(last) column becomes a column right before the decoding(first) column. The reference input signal given at a decoding column is propagated to the whole network while Its magnitude is reduced by the amount of a error metric on each branch. The circuit-based decoding is done by adding a trigger signals of same magnitudes to disconnect the path corresponding to logic 0 (or 1) and by observing its effect at an output column (the former column of the decoding column). The proposed Viterbi decoder has advantages in that it is operated with better performance of error correction, has a shorter latency and requires no path memories. The performance of error correction with the proposed Viterbi decoder is tested via the software simulation.

아날로그 셀룰라 병렬 처리 회로망(CPPN)을 이용한 Pattern Classification (Pattern Classification with the Analog Cellular Parallel Processing Networks)

  • 오태완;이혜정;김형석
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.2367-2370
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    • 2003
  • A fast pattern classification algorithm with Cellular Parallel Processing Network-based dynamic programming is proposed. The Cellular Parallel Processing Networks is an analog parallel processing architecture and the dynamic programming is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast Pattern classification with optimization is formed. On such CPPN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.

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