Optimal Filtering of a Gaussian Signal in the Presence of Lévy Noise
نویسندگان
چکیده
Many engineering applications require extracting a signal from observations corrupted by additive noise, possibly heavy-tailed. We assume that the observation noise is a Levy process, while the signal is Gaussian, and derive a non-linear recursive filter that minimizes the L error. A sub-optimal filter is proposed for numerical purposes, and simulations show that it out-performs the existing linear filter.
منابع مشابه
Using a novel method for random noise reduction of seismic records
Random or incoherent noise is an important type of seismic noise, which can seriously affect the quality of the data. Therefore, decreasing the level of this category of noises is necessary for increasing the signal-to-noise ratio (SNR) of seismic records. Random noises and other events overlap each other in time domain, which makes it difficult to attenuate them from seismic records. In this r...
متن کاملEffect of Post-Reconstruction Gaussian Filtering on Image Quality and Myocardial Blood Flow Measurement with N-13 Ammonia PET
Objective(s): In order to evaluate the effect of post-reconstruction Gaussian filtering on image quality and myocardial blood flow (MBF) measurement by dynamic N-13 ammonia positron emission tomography (PET), we compared various reconstruction and filtering methods with image characteristics. Methods: Dynamic PET images of three patients with coronary artery disease (male-female ratio of 2:1; a...
متن کاملSpeech Enhancement using Laplacian Mixture Model under Signal Presence Uncertainty
In this paper an estimator for speech enhancement based on Laplacian Mixture Model has been proposed. The proposed method, estimates the complex DFT coefficients of clean speech from noisy speech using the MMSE estimator, when the clean speech DFT coefficients are supposed mixture of Laplacians and the DFT coefficients of noise are assumed zero-mean Gaussian distribution. Furthermore, the MMS...
متن کاملSpeech Enhancement Using Gaussian Mixture Models, Explicit Bayesian Estimation and Wiener Filtering
Gaussian Mixture Models (GMMs) of power spectral densities of speech and noise are used with explicit Bayesian estimations in Wiener filtering of noisy speech. No assumption is made on the nature or stationarity of the noise. No voice activity detection (VAD) or any other means is employed to estimate the input SNR. The GMM mean vectors are used to form sets of over-determined system of equatio...
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 کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- SIAM Journal of Applied Mathematics
دوره 60 شماره
صفحات -
تاریخ انتشار 1999