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Track-to-track association is a fundamental problem in multi-sensor data fusion, which is complicated by random errors, false alarms, missed detections, and most profoundly, individual sensor bias. The state-of-the-art approach is to deal with bias estimates and track-to-track association jointly. However, the complexity of this approach is infeasible in the presence of a large number of targets....
In this paper, based on a matrix factorization a novel structure is proposed for digital system implementation and adaptive filtering applications. The equivalent state-space realization of such a structure is an input-balanced realization. Like the normalized lattice structure, it contains a series of Givens rotations. This proposed structure is simpler than the normalized structure and can be implemented...
Trajectory planning of robot is to control the robot in order to accurately follow the target track. And the target trajectory is always high-order and nonlinear. But RBF neural network can be achieved from the input to the output of arbitrary nonlinear mapping, through network learning and training to achieve the nonlinear function. This paper establishes a RBF neural network model firstly, and carries...
How to improve the whole processing capability, the availability and survivability of network by use of load balancing is studied in this paper. To solve the problem with dynamic traffic, a novel dynamic weight based traffic sharing (DW-TS) algorithm is proposed. In DW-TS, we introduce the idea of traffic engineering algorithm-minimum interference routing algorithm (MIRA) in generalized multi-protocol...
In engineering applications, piezoelectric materials are usually bonded to elastic substrates to form so-called smart materials and structures. Such materials and structures can respond to external electromechanical environments. This article studies a piezoelectric layer bonded to an elastic substrate subjected to static electromechanical loads, both of which are of finite length. A system of differential...
In this paper, we present a novel algorithm for FRFT with zooming-in ability, which is preferable to previous algorithms because it can freely choose computational resolution and zoom in on any interested portion of the fractional spectra, meanwhile, retains the advantage of the Ozaktas algorithm in computational speed. Its advantages in scrutinizing the fine structure of the partial spectra and improving...
This paper presents a new algorithm to estimate the cyclo-period of a poly-cyclo-stationary signal. The algorithm is essentially based on the time-varying correlation and the variability method; a calculation of the sample variance ratio as a function of the modulated noise variance visually reveals a regular pattern, from which the poly-cyclo-period is obtained. Properties of the estimation method...
We present a novel algorithm combining artificial neural networks and swarm intelligence (SI) methods to infer network interactions. The algorithm uses ant colony optimization (ACO) to identify the optimal architecture of a recurrent neural network (RNN), while the weights of the RNN are optimized using particle swarm optimization (PSO). Our goal is to construct an RNN that mimics the true structure...
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