Delay Estimator and Improved Proportionate Multi-Delay Adaptive Filtering Algorithm

This paper pertains to speech and acoustic signal processing, and particularly to a determination of echo path delay and operation of echo cancellers. To cancel long echoes, the number of weights in a conventional adaptive filter must be large. The length of the adaptive filter will directly affect both the degree of accuracy and the convergence speed of the adaptation process. We present a new adaptive structure which is capable to deal with multiple dispersive echo paths. An adaptive filter according to the present invention includes means for storing an impulse response in a memory, the impulse response being indicative of the characteristics of a transmission line. It also includes a delay estimator for detecting ranges of samples within the impulse response having relatively large distribution of echo energy. These ranges of samples are being indicative of echoes on the transmission line. An adaptive filter has a plurality of weighted taps, each of the weighted taps having an associated tap weight value. A tap allocation/control circuit establishes the tap weight values in response to said detecting means so that only taps within the regions of relatively large distributions of echo energy are turned on. Thus, the convergence speed and the degree of estimation in the adaptation process can be improved

Effects of Multirate Systems on the Statistical Properties of Random Signals

In multirate digital signal processing, we often encounter time-varying linear systems such as decimators, interpolators, and modulators. In many applications, these building blocks are interconnected with linear filters to form more complicated systems. It is often necessary to understand the way in which the statistical behavior of a signal changes as it passes through such systems. While some issues in this context have an obvious answer, the analysis becomes more involved with complicated interconnections. For example, consider this question: if we pass a cyclostationary signal with period K through a fractional sampling rate-changing device (implemented with an interpolator, a nonideal low-pass filter and a decimator), what can we say about the statistical properties of the output? How does the behavior change if the filter is replaced by an ideal low-pass filter? In this paper, we answer questions of this nature. As an application, we consider a new adaptive filtering structure, which is well suited for the identification of band-limited channels. This structure exploits the band-limited nature of the channel, and embeds the adaptive filter into a multirate system. The advantages are that the adaptive filter has a smaller length, and the adaptation as well as the filtering are performed at a lower rate. Using the theory developed in this paper, we show that a matrix adaptive filter (dimension determined by the decimator and interpolator) gives better performance in terms of lower error energy at convergence than a traditional adaptive filter. Even though matrix adaptive filters are, in general, computationally more expensive, they offer a performance bound that can be used as a yardstick to judge more practical "scalar multirate adaptation" schemes

Optimal adaptive filter realizations for sampled stochastic processes with an unknown parameter

Optimal adaptive filter for sampled stochastic processes with unknown paramete

Adaptive acoustooptic filter

A new adaptive filter utilizing acoustooptic devices in a space integrating architecture is described. Two configurations are presented; one of them, suitable for signal estimation, is shown to approximate the Wiener filter, while the other, suitable for detection, is shown to approximate the matched filter

A stochastic gradient adaptive filter with gradient adaptive step size

Journal ArticleAbstract-This paper presents an adaptive step-size gradient adaptive filter. The step size of the adaptive filter is changed according to a gradient descent algorithm designed to reduce the squared estimation error during each iteration. An approximate analysis of the performance of the adaptive filter when its inputs are zero mean, white, and Gaussian and the set of optimal coefficients are time varying according to a random walk model is presented in the paper. The algorithm has very good convergence speed and low steady-state misadjustment. Furthermore, the tracking performance of these algorithms in nonstationary environments is relatively insensitive to the choice of the parameters of the adaptive filter and is very close to the best possible performance of the least mean square (LMS) algorithm for a large range of values of the step size of the step size adaptation algorithm. Several simulation examples demonstrating the good properties of the adaptive filter as well as verifying the analytical results are also presented in the paper

Spectral breast CT : effect of adaptive filtration on CT numbers, CT noise, and CT dose

Purpose: Adaptive filtration facilitates spectral breast CT by decreasing count rate and dynamic range requirements of photon counting detectors. This project investigated the effect of adaptive filtration on beam hardening, CT numbers, noise, and dose in dedicated breast CT. Methods: Adaptive filters were simulated to provide a flat fluence at the detector surface when used with a 14 cm breast phantom at 120 kVp. Beam hardening with each filter type was measured against increasing x-ray beam half-fan angle.. Breast CT images were simulated with and without an adaptive filter in the beam at multiple tube voltages. CT number, noise, and contrast to noise ratio (CNR) were measured for contrast elements inside the phantom. Finally, dose measurements were performed with and without an adaptive filter to determine its effect on breast dose. Results: Acrylic filters, while larger in size, provided a more uniform spectral distribution across the detector field of view compared to other filters tested. Without the adaptive filter in the beam, CT numbers, noise and CNR of the contrast elements were non-uniform across the CT images, and became uniform when the adaptive filter was used. When combining an adaptive filter and scaled x-ray exposure, the CNR increased and became comparable to or higher than the CNR without using an adaptive filter. Measurements showed breast dose distributions were more spatially uniform with an adaptive filter than without. Furthermore, the dose distribution across the phantom with the adaptive filter was more uniform at lower tube voltages than at higher tube voltages. Conclusion: We concluded the filter material should be similar to breast tissue with respect to the attenuation coefficients and density. Acrylic adaptive filters provided the flattest intensity with minimal beam hardening for the 14 cm breast phantom. Finally, breast dose uniformity with filter was comparable or better than without filter