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On the optimal frame size of linear prediction techniques

机译:关于线性预测技术的最佳帧大小

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摘要

Loss of data in Communication Systems is a major problem. The main sources of data loss include congestion, sensor faults, mismatch of measuring devices and limited memory of the buffer registers. Three linear prediction (LP) techniques i.e. Normal Equation method, Levinson Durbin Algorithm (LDA) and Leroux Gueguen Algorithm (LGA) are used to predict the missing data. The objective of this paper is to analyze the three linear prediction techniques for both internal and external prediction and the effect of frame size on different parameters i.e. computational time, prediction gain and prediction error is also being analyzed. The LP algorithms are modified and a threshold limit for prediction error is set to keep the error bounded. A sub-optimal frame size is selected for all the three LP methods and in the end the three algorithms are compared for efficient performance.
机译:通信系统中的数据丢失是一个主要问题。数据丢失的主要来源包括拥塞,传感器故障,测量设备不匹配以及缓冲寄存器的有限存储。三种线性预测(LP)技术,即正态方程法,Levinson Durbin算法(LDA)和Leroux Gueguen算法(LGA)用于预测丢失的数据。本文的目的是分析内部和外部预测的三种线性预测技术,以及帧大小对不同参数(即计算时间,预测增益和预测误差)的影响。修改了LP算法,并设置了预测误差的阈值限制以保持误差范围。为所有三种LP方法选择了次优的帧大小,最后比较了这三种算法以提高性能。

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