The parity space approach to fault detection and isolation (FDI) has been developed during
the last 20 years, and the focus here is to describe its application to stochastic systems. A …

We have some time ago noticed that finding a book dealing with topics in the advanced
theory and applications of signal detection is not quite an easy matter. This is contrasted with …

In this paper, we propose a threshold-system-based detector (TD) for detecting a known
deterministic signal in independent non-Gaussian noise whose probability density function …

A fractional order moments-based detector is proposed for the detection of weak signals in
additive impulsive noise environment assumed as generalized Gaussian distribution with …

Current visualization systems are typically based on the concept of interactive post-
processing. This decoupling of data visualization from the process of data generation offers …

In this paper, we address the problem of spectrum sensing in the presence of non-Gaussian
noise for cognitive radio networks. A novel Rao test based detector, which does not require …

We address the problem of detecting the presence of wideband point sources and/or
estimating their location using data collected by an array of sensors. This passive …

Signal detection and modulation classification are becoming increasingly important in a
variety of wireless communication systems such as those involving spectrum management …

混合高斯Rao 有效绩检验是实现有色非高斯背景下微弱信号检测的渐近最佳检测器,
预白化和高斯化技术的应用使得它的检测性优于传统的匹配滤波器. 在使用混合高斯自回归模型 …

A machine learning approach is presented for detecting unknown or anomalous signals in a
complicated background of interfering signals and noise. The approach can be employed in …