A Variational Bayes Framework for Sparse Adaptive Estimation

نویسندگان
چکیده

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Compressive Sensing for Cluster Structured Sparse Signals: Variational Bayes Approach

Compressive Sensing (CS) provides a new paradigm of sub-Nyquist sampling which can be considered as an alternative to Nyquist sampling theorem. In particular, providing that signals are with sparse representations in some known space (or domain), information can be perfectly preserved even with small amount of measurements captured by random projections. Besides sparsity prior of signals, the i...

متن کامل

Variational Bayes Estimation of Mixing Coefficients

We investigate theoretically some properties of variational Bayes approximations based on estimating the mixing coefficients of known densities. We show that, with probability 1 as the sample size n grows large, the iterative algorithm for the variational Bayes approximation converges locally to the maximum likelihood estimator at the rate of O(1/n). Moreover, the variational posterior distribu...

متن کامل

Improved variational Bayes inference for transcript expression estimation.

RNA-seq studies allow for the quantification of transcript expression by aligning millions of short reads to a reference genome. However, transcripts share much of their sequence, so that many reads map to more than one place and their origin remains uncertain. This problem can be dealt using mixtures of distributions and transcript expression reduces to estimating the weights of the mixture. I...

متن کامل

BAYES ESTIMATION USING A LINEX LOSS FUNCTION

This paper considers estimation of normal mean ? when the variance is unknown, using the LINEX loss function. The unique Bayes estimate of ? is obtained when the precision parameter has an Inverse Gaussian prior density

متن کامل

Sparse signals estimation for adaptive sampling

This paper presents an estimation procedure for sparse signals in adaptive setting. We show that when the pure signal is strong enough, the value of loss function is asymptotically the same as for an optimal estimator up to a constant multiplier.

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

ژورنال

عنوان ژورنال: IEEE Transactions on Signal Processing

سال: 2014

ISSN: 1053-587X,1941-0476

DOI: 10.1109/tsp.2014.2338839