Reducing noise in the time-frequency representation using sparsity promoting kernel design
نویسندگان
چکیده
Missing samples in the time domain introduce noise-like artifacts in the ambiguity domain due to their de facto zero values assumed by the bilinear transform. These artifacts clutter the dual domain of the time-frequency signal representation and obscures the time-frequency signature of single and multicomponent signals. In order to suppress the artifacts influence, we formulate a problem based on the sparsity aware kernel. The proposed kernel design is more robust to the artifacts caused by the missing samples.
منابع مشابه
Speech Enhancement using Adaptive Data-Based Dictionary Learning
In this paper, a speech enhancement method based on sparse representation of data frames has been presented. Speech enhancement is one of the most applicable areas in different signal processing fields. The objective of a speech enhancement system is improvement of either intelligibility or quality of the speech signals. This process is carried out using the speech signal processing techniques ...
متن کاملClustering Noisy Signals with Structured Sparsity Using Time-Frequency Representation
We propose a simple and efficient time-series clustering framework particularly suited for low Signalto-Noise Ratio (SNR), by simultaneous smoothing and dimensionality reduction aimed at preserving clustering information. We extend the sparse K-means algorithm by incorporating structured sparsity, and use it to exploit the multi-scale property of wavelets and group structure in multivariate sig...
متن کاملVoice-based Age and Gender Recognition using Training Generative Sparse Model
Abstract: Gender recognition and age detection are important problems in telephone speech processing to investigate the identity of an individual using voice characteristics. In this paper a new gender and age recognition system is introduced based on generative incoherent models learned using sparse non-negative matrix factorization and atom correction post-processing method. Similar to genera...
متن کاملA sparsity-perspective to quadratic time-frequency distributions
We examine nonstationary signals within the framework of compressive sensing and sparse reconstruction. Most of these signals, which arise in numerous applications, exhibit small relative occupancy in the time-frequency domain, casting them as sparse in a joint-variable representation. We present two general approaches to incorporate sparsity into time-frequency analysis, leading to what we ref...
متن کاملDetecting pitting corrosion and its severity using wavelet entropy in electrochemical noise measurement
Entropy as a measure of uncertainty was used to represent the results of the wavelet technique in electrochemical noise analysis. The experimental signals were obtained by recording the electrochemical potential and current noise of 7075 aluminum alloy in 3.5% NaCl solution. The electrochemical potential and current noise were decomposed into 16 levels using Daubechies wavelets. Wavelet output ...
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 2014