Compressive Sensing
نویسنده
چکیده
منابع مشابه
Compressive Sensing and Information Theory
In a series of recent work [5, 4], the theory of compressive sensing has been examined from an information theory perspective. Novel results regarding noisy compressive sensing have been found while viewing the compressive sensing problem as a communication channel. This perspective led to a new approach of solving the compressive sensing problem through a Bayesian approach. Belief propagation,...
متن کاملSTCS-GAF: Spatio-Temporal Compressive Sensing in Wireless Sensor Networks- A GAF-Based Approach
Routing and data aggregation are two important techniques for reducing communication cost of wireless sensor networks (WSNs). To minimize communication cost, routing methods can be merged with data aggregation techniques. Compressive sensing (CS) is one of the effective techniques for aggregating network data, which can reduce the cost of communication by reducing the amount of routed data to t...
متن کاملMeasure What Should be Measured: Progress and Challenges in Compressive Sensing
Is compressive sensing overrated? Or can it live up to our expectations? What will come after compressive sensing and sparsity? And what has Galileo Galilei got to do with it? Compressive sensing has taken the signal processing community by storm. A large corpus of research devoted to the theory and numerics of compressive sensing has been published in the last few years. Moreover, compressive ...
متن کاملCompressive Sensing in Holography
Compressive sensing provides a new framework for simultaneous sampling and compression of signals. According to compressive sensing theory one can recover compressible signals and images from far fewer samples or measurements that traditional methods use. Applying compressive sensing theory for holography comes natural since three-dimensional (3D) data is typically very redundant, thus it is al...
متن کاملAn overview of compressive sensing techniques applied in holography
In recent years compressive sensing has been successfully introduced in digital holography. Depending on the ability to sparsely represent an object, the compressive sensing paradigm provides an accurate object reconstruction framework, from a relatively small number of encoded signal samples. Digital holography has been proven to be an efficient and physically realizable sensing modality that ...
متن کاملDeterministic Sensing Matrices in Compressive Sensing: A Survey
Compressive sensing is a sampling method which provides a new approach to efficient signal compression and recovery by exploiting the fact that a sparse signal can be suitably reconstructed from very few measurements. One of the most concerns in compressive sensing is the construction of the sensing matrices. While random sensing matrices have been widely studied, only a few deterministic sensi...
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