In the past of two decades, wavelet methods have been adopted enthusiastically in many engineering applications such as signal and image processing. However, like most of the classic orthogonal expansions, wavelet expansions also exhibit Gibbs phenomenon around discontinuities of the original signals. Therefore, the recovered signals using wavelet expansions could be corrupted by the overshoot ...

This paper explores the design of time-limited input-output waveforms, the outputs being orthogonal, for band-limited channels, whose characteristics are known apriori. Hence, the channel can support baseband multiplexed transmission without Intersymbol Interference. The problem has been worked out for two cases of channel modeling the rational transfer function channel model and the distribute...

On [24] some consequences of the Restricted Isometry Property (RIP) of matrices have been applied to develop a greedy algorithm called “ROMP” (Regularized Orthogonal Matching Pursuit) to recover sparse signals and to approximate non-sparse ones. These consequences were subsequently applied to other greedy and thresholding algorithms like “SThresh”, “CoSaMP”, “StOMP” and “SWCGP”. In this paper, ...

A novel radio channel compensation method aiming to give optimal calibration for microstrip antenna array systems is presented in this paper, realized for an actual DOA measurement antenna system using microstrip antennas to sample the electromagnetic field, operating at 4.5GHz. This new approach considers mismatch between antennas and channel RF ports, channel transmission inequalities, and al...

Given a finite set of linearly independent quantum states, an observer who examines a single quantum system may sometimes identify its state with certainty. However, unless these quantum states are orthogonal, there is a finite probability of failure. A complete solution is given to the problem of optimal distinction of three states, having arbitrary prior probabilities and arbitrary detection ...

We present a composite Compressed Sensing system for the acquisition and recovery of compressible signals, where sparse Binary Matrix aids Sparsity Order Estimation, Gaussian reconstruction. The is deterministic adapted according to varying nature sparsity order. estimate order by exploiting structure statistics obtained measurements. refine estimates using Kalman filter with discrete Markov mo...

In this paper a new method for adaptive synthesis of a smooth orthogonal wavelet, using fast neural network and genetic algorithm, is introduced. Orthogonal lattice structure is presented. A new method of supervised training of fast neural network is introduced to synthesize a wavelet with desired energy distribution between output signals from low–pass and high–pass filters on subsequent level...

Recent studies have shown that sparse representation can be used effectively as a prior in linear inverse problems. However, in many multiscale bases (e.g. wavelets), signals of interest (e.g. piecewisesmooth signals) not only have few significant coefficients, but also those significant coefficients are well-organized in trees. We propose to exploit this prior, named sparse-tree, for linear in...

Reduced-order mass weighted proper orthogonal decomposition (RMPOD), smooth orthogonal decomposition (SOD), and state variable modal decomposition (SVMD) are used to extract modal parameters from a nonuniform experimental beam. The beam was sensed by accelerometers. Accelerometer signals were integrated and passed through a high-pass filter to obtain velocities and displacements, all of which w...

In this paper, we investigate the performance of a downlink multiple-input multiple-output (MIMO) multicarrier code division multiple access (MC-CDMA) system employing a receiver with iterative channel estimation (ICE). The MC-CDMA system transmits several data symbols per user and per orthogonal frequency division multiplexing (OFDM) symbol in parallel, with each data symbol being spread with ...