منابع مشابه
From Blind Quantum Source Separation to Blind Quantum Process Tomography
We here extend the field of blind (i.e. unsupervised) quantum computation into two directions. On the one hand, we introduce a new class of blind quantum source separation (BQSS) methods, which perform quantum/classical data conversion by means of spin component measurements, followed by classical processing. They differ from our previous class of classical-processing BQSS methods by using exte...
متن کاملBlind deconvolution in optical diffusion tomography.
We use blind deconvolution methods in optical diffusion tomography to reconstruct images of objects imbedded in or located behind turbid media from continuous-wave measurements of the scattered light transmitted through the media. In particular, we use a blind deconvolution imaging algorithm to determine both a deblurred image of the object and the depth of the object inside the turbid medium. ...
متن کاملBlind Spectrum Sensing Techniques for Cognitive Radio System
As the mobile communication environments grow rapidly, much attention has been paid on the use of spectrum resources. Recently, a new technology called Cognitive Radio (CR) was developed for using the unused spectrum bands efficiently. In the CR system, one possible way to locate these unused spectrum bands is to use so-called spectrum sensing. This technique, however, should be computationally...
متن کاملA Blind Detection Algorithm Utilizing Statistical Covariance in Cognitive Radio
As the expression of performance parameters are obtained using asymptotic method in most blind covariance detection algorithm, the paper presented a new blind detection algorithm using cholesky factorization. Utilizing random matrix theory, we derived the performance parameters using non-asymptotic method. The proposed method overcomes the noise uncertainty problem and performs well without any...
متن کاملBlind Separation of Radio Signals in Fading Channels
In We apply information maximization / maximum likelihood blind source separation [2, 6) to complex valued signals mixed with complex valued nonstationary matrices. This case arises in radio communications with baseband signals. We incorporate known source signal distributions in the adaptation, thus making the algorithms less "blind". This results in drastic reduction of the amount of data nee...
متن کاملذخیره 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: 2018
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2018.2799169