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In this paper, we consider the problem of distributed detection of sparse signals with a sensor network. Due to practical constraints on communication bandwidth and computational capacity, detection of sparse signals in a distributed manner is more efficient than centralized processing in terms of communication and computation. We develop a greedy algorithm named distributed subspace pursuit (DSP)...
A robust reduced-rank adaptive beamforming method based on the joint iterative optimization direction-adaptive (JIO-DA) scheme is developed for the large array scenarios based on the linear constraint minimum variance (L-CMV) criterion. The JIO-DA scheme jointly optimizes a reduced-rank filter and a transforming matrix. The columns of the transforming matrix are considered as direction vectors and...
Sparse signals can be sensed with a reduced number of projections and then reconstructed if compressive sensing is employed. Traditionally, the projection matrix is chosen as a random matrix, but a projection sensing matrix that is optimally designed for a certain class of signals can further improve the reconstruction accuracy. This paper considers the problem of designing the projection matrix Φ...
Mean shift, like other gradient ascent optimization methods, is susceptible to local maxima, and hence often fails to find the desired global maximum. For this reason, mean shift segmentation algorithm based on bacterial colony chemotaxis (BCC) is proposed in this paper. The mean shift vector is firstly optimized using BCC algorithm. Then, the optimal mean shift vector is updated using mean shift...
This paper deals with low complexity digital filter structures with consideration of maximizing a newly defined structure robustness measure. Two classes of efficient lattice-based filter structures are considered. For an Nth order digital filter, the structures in these classes all have 2N + 1 multipliers. The expression of robustness measure is derived and the optimum structure problem is formulated...
In this paper, a new method is proposed to optimize the projection matrix, which, unlike the existing approaches, attempts to choose the projection matrix such that the sensing matrix is as close to a tight frame/equiangular tight frame as possible. In the proposed method, there are two important procedures that are used to adjust the Gram matrix of the sensing matrix. The simulation results are presented...
This paper aims to present a method to design the optimization steady state nonlinear controller of turbofan engine which is applicable for the whole flight envelop. First, based on the linear small deviation mathematical models of some representative operation points of turbofan in various flight conditions, the linear quadratic regulators of turbofan are designed respectively and the optimization...
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