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Showing 1 to 11 of 11 for “"sampling theorem"”.

  1. Building compressed sensing systems : sensors and analog-to-information converters

    … than ordinarily used in the Shannon's sampling theorem [14]. Introducing the CS theory has sparked interest in designing new hardware architectures which can be potential substitutions for traditional architectures in communication systems. CS-based wireless sensors and …

    mit Repository record for Building compressed sensing systems : sensors and analog-to-information converters (opens in a new tab)

  2. Wavelets and filter banks: New results and applications

    … reduction of the multidimensional rational sampling rate filter bank problem to the uniform sampling rate filter bank problem, solution to the completion problem for filter banks (by reducing it to the (YJBK) parameterization problem in control theory) etc. Perfect reconstruction filter …

    rice Repository record for Wavelets and filter banks: New results and applications (opens in a new tab)

  3. Adaptive sampling for multiscale environmental sensor networks

    … both temporally and spatially. Without effective sampling logic, these powerful tools can produce an overwhelming quantity of data that may not capture the most valuable information for scientific discovery. To address this issue, this research expands the definition of a “hot moment”, a term …

    uiuc Repository record for Adaptive sampling for multiscale environmental sensor networks (opens in a new tab)

  4. A hardware platform to test analog-to-information conversion and non-uniform sampling

    The Nyquist-Shannon sampling theorem tells us that in order to fully recover a band-limited signal previously converted to discrete data points, said signal must have been sampled at a frequency greater than twice its bandwidth. This theorem puts a burden on circuits like ADCs, in the sense that …

    mit Repository record for A hardware platform to test analog-to-information conversion and non-uniform sampling (opens in a new tab)

  5. Low Latency Compressive Sensing using Multi-Resolution Analysis In Radar Signal Processing

    … a wider signal bandwidth. The Shannon/Nyquist sampling theorem states, the ADC must sample the signal at a rate two times faster than the signal bandwidth in order to avoid data loss. However, the advances of ADC cannot always meet these demands. Considerable research has been done to find new …

    carleton Repository record for Low Latency Compressive Sensing using Multi-Resolution Analysis In Radar Signal Processing (opens in a new tab)

  6. Fast MRI with sparse sampling: models, algorithms, and applications

    … (MRI) methods are based on the Shannon-Nyquist sampling theorem. The number of required Nyquist samples grows exponentially with respect to the underlying physical dimension of the imaging problem, resulting in significant difficulty of achieving high resolution for higher-dimensional imaging …

    uiuc Repository record for Fast MRI with sparse sampling: models, algorithms, and applications (opens in a new tab)

  7. Some Notes on Compressive Sensing

    … in this thesis. The basic principle of Nyquist sampling theory has been one of the conventional ways in data acquisition and reconstruction signals and images. This so-called principle, introduces a minimum rate at which a signal can be sampled to be reconstructed without any errors. On the …

    unm Repository record for Some Notes on Compressive Sensing (opens in a new tab)

  8. Compressive sensing of images and video: towards low-complexity, real-time operation

    … than samples required by the classical Nyquist sampling theorem, at the cost of more computationally intensive reconstruction. Video Block Compressive Sensing (VBCS), using a Multi Pixel Camera (MPC), divides the sensed image into blocks reducing storage requirements, and allowing lower latency …

    cambridge Repository record for Compressive sensing of images and video: towards low-complexity, real-time operation (opens in a new tab)

  9. Compressive Detection and Estimation with Applications to Cognitive Radio and Radar

    According to Nyquist Sampling theorem, a band-limited signal can be reconstructed accurately if the sampling rate exceeds twice the maximum frequency of the signal. In many scenarios, this Nyquist sampling rate cannot be achieved due to hardware limitations. Compressive sensing (CS) is a technique …

    washington Repository record for Compressive Detection and Estimation with Applications to Cognitive Radio and Radar (opens in a new tab)

  10. Global optimization methods for localization in compressive sensing

    … a few terms from a basis expansion) by using a sampling rate much lower than that required by the Nyquist-Shannon sampling theorem (i.e., twice the highest frequency present in the signal of interest). Low-rate sampling reduces implementation's constraints and translates into cost savings due to …

    njit Repository record for Global optimization methods for localization in compressive sensing (opens in a new tab)