{"title":"Aliasing probability for multiple input signature analyzers with dependent inputs","authors":"T. W. Williams, W. Daehn","doi":"10.1109/CMPEUR.1989.93497","DOIUrl":null,"url":null,"abstract":"The authors consider the aliasing probability in multiple-input data compressors used in self-testing networks. It is shown that a far more general class of linear machines, linear-feedback shift registers can be used for data-compression purposes. The steady-state value of the aliasing probability is independent of the correlation of the data streams at the inputs of the data compressor. The function of these machines is modeled by a Markov process. The aliasing probability is the same as for the well-understood signature analysis registers with a single input. An easy-to-check criterion is given to decide whether a given linear machine falls into this class of multiple-input data compressors. Two special kinds of circuits are analyzed in more detail with respect to their aliasing properties: linear-feedback shift registers with multiple inputs and linear cellular automata. Simulation results show the effect of the next state function on the steady-state value of the aliasing probability and the effect of correlation on the transient.<<ETX>>","PeriodicalId":304457,"journal":{"name":"Proceedings. VLSI and Computer Peripherals. COMPEURO 89","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. VLSI and Computer Peripherals. COMPEURO 89","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMPEUR.1989.93497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
The authors consider the aliasing probability in multiple-input data compressors used in self-testing networks. It is shown that a far more general class of linear machines, linear-feedback shift registers can be used for data-compression purposes. The steady-state value of the aliasing probability is independent of the correlation of the data streams at the inputs of the data compressor. The function of these machines is modeled by a Markov process. The aliasing probability is the same as for the well-understood signature analysis registers with a single input. An easy-to-check criterion is given to decide whether a given linear machine falls into this class of multiple-input data compressors. Two special kinds of circuits are analyzed in more detail with respect to their aliasing properties: linear-feedback shift registers with multiple inputs and linear cellular automata. Simulation results show the effect of the next state function on the steady-state value of the aliasing probability and the effect of correlation on the transient.<>
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