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unsatisfactory

  • An unsatisfactory property of particle filters is that they may become inefficient when the observa

    An unsatisfactory property of particle filters is that they may become inefficient when the observation noise is low. In this paper we consider a simple-to-implement particle filter, called ‘LIS-based particle filter’, whose aim is to overcome the above mentioned weakness. LIS-based particle filters sample the particles in a two-stage process that uses information of the most recent observation, too. Experiments with the standard bearings-only tracking problem indicate that the proposed new particle filter method is indeed a viable alternative to other methods.

    標(biāo)簽: unsatisfactory inefficient property particle

    上傳時(shí)間: 2014-01-11

    上傳用戶:大三三

  • Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assum

    Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assuming BPSK. Brute force Monte Carlo approach is unsatisfactory (takes too long) to find the BER curve. The computation uses a quasi-analytic (QA) technique that relies on the estimation (approximate one) of the information-bits Weight Enumerating Function (WEF) using A simulation of the convolutional encoder. Once the WEF is estimated, the analytic formula for the BER is used.

    標(biāo)簽: convolutional Computes encoding decision

    上傳時(shí)間: 2013-12-24

    上傳用戶:咔樂塢

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