Seislet-based morphological component analysis using scale-dependent exponential shrinkage

نویسندگان

  • Pengliang Yang
  • Sergey Fomel
چکیده

Article history: Received 28 November 2014 Received in revised form 3 February 2015 Accepted 1 April 2015 Available online 13 April 2015

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Speech enhancement based on hidden Markov model using sparse code shrinkage

This paper presents a new hidden Markov model-based (HMM-based) speech enhancement framework based on the independent component analysis (ICA). We propose analytical procedures for training clean speech and noise models by the Baum re-estimation algorithm and present a Maximum a posterior (MAP) estimator based on Laplace-Gaussian (for clean speech and noise respectively) combination in the HMM ...

متن کامل

Imaging effects due to multi-scale model heterogeneity

Velocity models used for wavefield-based seismic imaging represent approximations of the velocity characterizing the area under investigation. We can conceptually decompose the real velocity model into a background component which can be inferred using conventional velocity analysis techniques, and into another unknown component encapsulating the model heterogeneities. This unknown component is...

متن کامل

A Fault Diagnosis Method for Automaton based on Morphological Component Analysis and Ensemble Empirical Mode Decomposition

In the fault diagnosis of automaton, the vibration signal presents non-stationary and non-periodic, which make it difficult to extract the fault features. To solve this problem, an automaton fault diagnosis method based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD) was proposed. Based on the advantages of the morphological component analysis method i...

متن کامل

A Fault Diagnosis Method for Automaton Based on Morphological Component Analysis and Ensemble Empirical Mode Decomposition

In the fault diagnosis of automaton, the vibration signal presents non-stationary and non-periodic, which make it difficult to extract the fault features. To solve this problem, an automaton fault diagnosis method based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD) was proposed. Based on the advantages of the morphological component analysis method i...

متن کامل

Seislet transform and seislet frame a

We introduce a digital wavelet-like transform, which is tailored specifically for representing seismic data. The transform provides a multiscale orthogonal basis with basis functions aligned along seismic events in the input data. It is defined with the help of the wavelet lifting scheme combined with local planewave destruction. In the 1-D case, the seislet transform is designed to follow loca...

متن کامل

ذخیره 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 2015