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Passive source localization is one of the issues in array signal processing fields. In some practical applications, the signals received by an array are the mixture of near-field and far-field sources, such as speaker localization using microphone arrays and guidance (homing) systems. To localize mixed near-field and far-field sources, this paper develops a(More)
A novel higher order singular value decomposition (HOSVD)-based image fusion algorithm is proposed. The key points are given as follows: 1) Since image fusion depends on local information of source images, the proposed algorithm picks out informative image patches of source images to constitute the fused image by processing the divided subtensors rather(More)
The steady-state excess mean square error (EMSE) of the adaptive filtering under the maximum correntropy criterion (MCC) has been studied. For Gaussian noise case, we establish a fixed-point equation to solve the exact value of the steady-state EMSE, while for non-Gaussian noise case, we derive an approximate analytical expression for the steady-state EMSE,(More)
In this paper, the problem of source localization in distributed multiple-input multiple-output (MIMO) radar using bistatic range measurements, which correspond to the sum of transmitter-to-target and target-to-receiver distances, is addressed. Our solution is based on the Lagrange programming neural network (LPNN), which is an analog neural computational(More)
This paper proposes a new cumulant-based algorithm to jointly estimate four-dimensional (4D) source parameters of multiple near-field narrowband sources. Firstly, this approach proposes a new cross-array, and constructs five high-dimensional Toeplitz matrices using the fourth-order cumulants of some properly chosen sensor outputs; secondly, it forms a(More)
Wireless sensor networks (WSNs) have been proposed for a multitude of location-dependent applications. To stamp the collected data and facilitate communication protocols, it is necessary to identify the location of each sensor. In this paper, we discuss the performance of two novel positioning schemes, which use two generalized geometrical localization(More)
This paper develops a distributed dictionary learning algorithm for sparse representation of the data distributed across nodes of sensor networks, where the sensitive or private data are stored or there is no fusion center or there exists a big data application. The main contributions of this paper are: 1) we decouple the combined dictionary atom update and(More)
To maximize the transmitted power available in active sensing, the probing waveform should be of constant modulus. On the other hand, in order to adapt to the increasingly crowed radio frequency spectrum and prevent mutual interferences, there are also requirements in the waveform spectral shape. That is to say, the waveform must fulfill constraints in both(More)
1. Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, 710049, China 2. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640, China 3. School of Automation & Information Engineering, Xi'an University of Technology, Xi'an 710048, China 4. Department of Electrical and(More)