Sampling (signal processing)
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The recently introduced continuous Skip-gram model is an efficient method for learning high-quality distributed vector… Expand Compressive sampling (CoSa) is a new paradigm for developing data sampling technologies. It is based on the principle that many… Expand Conventional sub-Nyquist sampling methods for analog signals exploit prior information about the spectral support. In this paper… Expand The Karhunen-Lo eve basis functions, more frequently referred to as principal components or empirical orthogonal functions (EOFs… Expand Conventional approaches to sampling signals or images follow Shannon's theorem: the sampling rate must be at least twice the… Expand The authors consider classes of signals that have a finite number of degrees of freedom per unit of time and call this number the… Expand The quintessential goal of sensor array signal processing is the estimation of parameters by fusing temporal and spatial… Expand 1. Introduction. 2. Discrete-Time Signals and Systems. 3. The Z-Transform and Its Application to the Analysis of LTI Systems. 4… Expand The Digital Signal Processing Group develops signal processing algorithms that span a wide variety of application areas including… Expand The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed… Expand