Stable Adaptive Nonstationary Signal Detection Based on the Robuston Scheme*
نویسندگان
چکیده
The mbuston scheme is a novel reduced-detail paradigm for nonstationary signal modelinglprocessing with enhanced statistical stability. Here, we apply the robuston scheme to the problem of detecting a nonstationary random signal in white Gaussian noise. We propose two different “robuston detectors” along with signal-adaptive online implementations that perform online estimation of the signal statistics from a ,single observation. The performance of adaptive robuston detectors is assessed through numerical simulations.
منابع مشابه
Robuston methods for stable statistical signal processing: principles and application to nonstationary signal estimation
We introduce e reduced-detail paradigm for nonstationary statistical signal processing with enhanced performance. Time-frequency localized subspace signal components (called robustons) are used as atomic entities for statistical signal modeling and processing. Robuston signal processing employs special time-varying filters that allow an efficient on-line implementation, and statistical signal d...
متن کاملA Novel Method for Automated Estimation of Effective Parameters of Complex Auditory Brainstem Response: Adaptive Processing based on Correntropy Concept
Objectives: Automated Auditory Brainstem Responses (ABR) peak detection is a novel technique to facilitate the measurement of neural synchrony along the auditory pathway through the brainstem. Analyzing the location of the peaks in these signals and the time interval between them may be utilized either for analyzing the hearing process or detecting peripheral and central lesions in the human he...
متن کاملAdaptive-Filtering-Based Algorithm for Impulsive Noise Cancellation from ECG Signal
Suppression of noise and artifacts is a necessary step in biomedical data processing. Adaptive filtering is known as useful method to overcome this problem. Among various contaminants, there are some situations such as electrical activities of muscles contribute to impulsive noise. This paper deals with modeling real-life muscle noise with α-stable probability distribution and adaptive filterin...
متن کاملReal-time damage detection of bridges using adaptive time-frequency analysis and ANN
Although traditional signal-based structural health monitoring algorithms have been successfully employed for small structures, their application for large and complex bridges has been challenging due to non-stationary signal characteristics with a high level of noise. In this paper, a promising damage detection algorithm is proposed by incorporation of adaptive signal processing and Artificial...
متن کاملAdaptive Segmentation with Optimal Window Length Scheme using Fractal Dimension and Wavelet Transform
In many signal processing applications, such as EEG analysis, the non-stationary signal is often required to be segmented into small epochs. This is accomplished by drawing the boundaries of signal at time instances where its statistical characteristics, such as amplitude and/or frequency, change. In the proposed method, the original signal is initially decomposed into signals with different fr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2004