Abstract
Multi-rate digital signal processing techniques have been developed in recent years for a wide range of applications, such as speech and image compression, statistical and adaptive signal processing and digital audio. Multi-rate statistical and adaptive signal processing methods provide solution to original signal reconstruction, using observation signals sampled at different rates. In this study, a signal reconstruction process by using the observation signals which are sampled at different sampling rates is presented. The results are compared with the least mean squares (LMS) and the normalized least mean squares (NLMS) methods. As the results indicate, the signal estimation obtained is much more efficient than the previous studies. Designed multi-rate scheme provides significant advantages in terms of error and estimation accuracy.
Highlights
Multi-rate signal processing is an integral part of the signal processing technique and has been developing rapidly during the last decade
Multi-rate signal processing methods focus on systems which include signals that are sampled at different rates
The periodicity is discussed in multi-rate systems because down and up sampling processes vary with time and they do not preserve stationarity
Summary
Multi-rate signal processing is an integral part of the signal processing technique and has been developing rapidly during the last decade. The authors utilize two signals with one having twice the sampling rate of the other to detect the coefficients of the random process. They show that the optimal filter is a linear filter whose coefficients change periodically for this particular problem. Authors in [8] found out a solution to the problem of reconstructing a high resolution signal from two low-rate sensors with time delay by using multi-rate measurements. An approach which uses suitable low resolution samples to estimate power spectral density of wide sense stationary random signal is developed in [19]. I propose to combine adaptive signal processing methods with multi-rate signal processing techniques to provide more efficient signal reconstruction.
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