Abstract Active sonar is used for target detection in the bistatic system. When approaches or crosses source-receiver line, direct blast will cause serious interference received signal. The adaptive filtering algorithm to suppress such as blast, and it implemented on FPGA by System Generator. results show that filter can effectively forward scattering signal submerged be displayed, underwater d...

Two-dimensional (TD) adaptive filtering is a technique that can be applied to many image, and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to TD structures and the novel TD adaptive filters are established. Based on this extension, the TD variable step-size normalized least mean squares (TD-VSS-NLMS), the TD-VSS affine projection algorithms (...

A novel procedure is described for accelerating the convergence of Markov chain Monte Carlo computations. The algorithm uses an adaptive bootstrap technique to generate candidate steps in the Markov Chain. It is efficient for symmetric, convex probability distributions, similar to multivariate Gaussians, and it can be used for Bayesian estimation or for obtaining maximum likelihood solutions wi...

Sensing the radio frequency bands is an open problem for dynamic spectrum access (DSA) in cognitive radio networks. To address this, numerous signal processing algorithms have been described based on entropy measurement. However, most of the methods lack connectivity between signal detection and appropriateness of the selected entropy. In this work, we propose an optimal detection method which ...

In this paper, a pop-click noise detection method is proposed to improve the quality of audio signals recorded using portable microphones. In order to reduce false alarm and missing detection errors, the proposed method utilizes the second-order difference of an uncorrelated residual signal, followed by adaptive median thresholding. It is shown from performance evaluation that the proposed meth...

In this study, detection and identification of common faults in industrial gas turbines is investigated. We propose a model-based robust fault detection(FD) method based on multiple models. For residual generation a bank of Local Linear Neuro-Fuzzy (LLNF) models is used. Moreover, in fault detection step, a passive approach based on adaptive threshold is employed. To achieve this purpose, the a...

Motivated by Signal Detection Theory (SDT), we developed a family of novel adaptive methods that estimate the sensitivity threshold-the signal intensity corresponding to a pre-defined sensitivity level (d' = 1)-in Yes-No (YN) and Forced-Choice (FC) detection tasks. Rather than focus stimulus sampling to estimate a single level of %Yes or %Correct, the current methods sample psychometric functio...