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The radial basis function network offers a viable alternative to the two-layer neural network in many applications of signal processing. A common learning algorithm for radial basis function networks is based on first choosing randomly some data points as radial basis function centers and then using singular-value decomposition to solve for the weights of(More)
The application of a radial basis function network to digital communications channel equalization is examined. It is shown that the radial basis function network has an identical structure to the optimal Bayesian symbol-decision equalizer solution and, therefore, can be employed to implement the Bayesian equalizer. The training of a radial basis function(More)
Multiple–antenna techniques constitute a key technology for modern wireless communications, which trade–off superior error performance and higher data rates for increased system complexity and cost. Among the many transmission principles that exploit multiple–antenna at either the transmitter, the receiver, or both, Spatial Modulation (SM) is a novel and(More)
A multi-stage blind clustering algorithm is proposed for equalisation of multi-level quadrature amplitute modulation (M-$AM) channels. A hierarchical decomposition divides the task of equalising a high-order QAM channel into much simpler sub-tasks. Each sub-task can be accomplished fast and reliably using a blind clustering algorithm derived originally for(More)
This paper considers a number of algorithms that could be used for antenna array receivers in the mobile–to–base station link of a cellular code division multiple access (CDMA) system. Two classes of algorithms are considered: 1) algorithms that estimate spatially matched filter solutions and 2) adaptive techniques for suppressing interference. In the(More)
—In this paper a novel detection algorithm for spatial modulation (SM) based on sphere decoder (SD) tree search idea is proposed. The aim is to reduce the receiver complexity of the existing optimal decoder while maintaining an optimum performance. The algorithm performs a maximum likelihood (ML) search, only over those points that lie inside a sphere,(More)