نتایج جستجو برای: compressed sampling
تعداد نتایج: 235888 فیلتر نتایج به سال:
In the classical Shannon/Nyquist sampling theorem, information is not lost in uniformly sampling a signal, signal must be sampled at least two times faster than its bandwidth. Because of the restriction of the Nyquist rate, it end up with too many samples in many applications, and it becomes a great challenge for further transmission and storage. In recent years, an emerging theory of signal ac...
In this paper, two methods are proposed which address the random sampling and compressed sensing recovery problems. The proposed random sampling recovery method is the Iterative Method with Adaptive Thresholding and Interpolation (IMATI). Simulation results indicate that the proposed method outperforms existing random sampling recovery methods such as Iterative Method with Adaptive Thresholding...
The usual paradigm for signal processing is to model a signal as a bandlimited function and capture the signal by means of its time samples. The Shannon-Nyquist theory says that the sampling rate needs to be at least twice the bandwidth. For broadbanded signals, such high sampling rates may be impossible to implement in circuitry. Compressed Sensing is a new area of signal processing whose aim ...
Compressed sensing is a recently developed signal acquisition technique. In contrast to traditional sampling methods, significantly fewer samples are required whenever the signals admit a sparse representation. Crucially, sampling methods can be constructed that allow the reconstruction of sparse signals from a small number of measurements using efficient algorithms. We have recently generalise...
Internet of Things is the network of interconnection between people and things, and between things themselves by embedding additional gadgets, such as sensors, RFID tags. Mass data are usually collected, transmitted, processed and stored in Internet of Things. In this paper, a novel sampling method, i.e. compressed sensing, is used in processing mass data in Internet of Things. Compressed sensi...
The advent of compressed sensing provides a new way to sample and compress signals. In this thesis, a parallel compressed sensing architecture is proposed, which samples a twodimensional reshaped multidimensional signal column by column using the same sensing matrix. Compared to architectures that sample a vector-reshaped multidimensional signal, the sampling device in the parallel compressed s...
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