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In the early 1960s research into radar signal synthesis produced important formulas describing the action of the two-dimensional Fourier transform on auto- and crossambiguity surfaces.
      
It is shown that the one-dimensional sampling sets correspond to Bessel sequences of complex exponentials that are not Riesz bases for $L^2[-R,R].$ A signal processing application in which such sampling sets arise naturally is described in detail.
      
Given a bandlimited signal, we consider the sampling of the signal and some of its derivatives in a periodic manner.
      
We present a method for finding the dual frame and, thereby, a method for reconstructing the signal from its samples.
      
We show that if no sampling of the signal itself is involved, the sampling is not stable and cannot be stabilized by oversampling.
      
Examples are considered, and the frame bounds in the case of sampling of the signal and its first derivative are calculated explicitly.
      
Finally, the matrix approach can be similarly applied to other problems of signal representation.
      
Our work builds on a uniqueness result for reconstructing an L2 signal from irregular sampling of its wavelet transform of Grochenig and the related work of Benedetto, Heller, Mallat, and Zhong.
      
Our work builds on a uniqueness result for reconstructing an L2 signal from irregular sampling of its wavelet transform of Gr?chenig and the related work of Benedetto, Heller, Mallat, and Zhong.
      
The Discrete Wavelet Transform (DWT) is of considerable practical use in image and signal processing applications.
      
A geometrical problem arising in a signal restoration algorithm
      
Its absolute value (|A(u)|) measures the correlation between the signal u emitted by the radar transmitter and its echo after reaching a moving target.
      
Therefore, it is also important to know to what extent |A(u)| determines the signal.
      
Such systems play an important role in time-frequency analysis and digital signal processing.
      
Connections to signal recovery for positive functions, as well as partial spectral analysis, are also discussed.
      
Prolate Spheroidal Wave Functions (PSWFs) are a well-studied subject with applications in signal processing, wave propagation, antenna theory, etc.
      
Spline Modulation of Sinusoids for Signal Representation
      
There are many advantages in the use of Hadamard matrices in digital signal
      
The chromatic expansions have properties which make them useful in fields involving empirically sampled data, such as signal processing.
      
In signal processing, communications, and other branches of information technologies, it is often desirable to map the higher-dimensional signals on Sn.
      
 

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