Time-domain spherical near-field formulas in the case where theradial components of the electromagnetic field are measured

Spherical near-field formulas in the time-domain are derived so that the electromagnetic field outside a given scan sphere can be found from measurements of the radial electric and magnetic field components on that scan sphere     

Sequential blind extraction of instantaneously mixed sources

This paper presents a general approach to sequential blind extraction of instantaneously mixed sources for several major ill-conditioned cases as well as the regular case of full column rank mixing matrices. Four ill-conditioned cases are considered: The mixing matrix is square but singular; the number of sensors is less than that of sources; the number of sensors is larger than that of sources, but the column rank of the mixing matrix is deficient; and the number of sources is unknown and the column rank of the mixing matrix is deficient. First, a solvability analysis is presented for a general case. A necessary and sufficient condition for extractability is derived. A sequential blind extraction approach is then proposed to extract all theoretically separable sources. Next, a principle and a cost function based on fourth-order cumulants are presented for blind source extraction. By minimizing the cost function under a nonsingularity constraint of the extraction matrix, all theoretically separable sources can be extracted sequentially. Finally, simulation results are presented to demonstrate the validity and performance of the blind source extraction approach     

Linear multichannel blind equalizers of nonlinear FIR Volterrachannels

Truncated Volterra expansions model nonlinear systems encountered with satellite communications, magnetic recording channels, and physiological processes. A general approach for blind deconvolution of single-input multiple-output Volterra finite impulse response (FIR) systems is presented. It is shown that such nonlinear systems can be blindly equalized using only linear FIR filters. The approach requires that the Volterra kernels satisfy a certain coprimeness condition and that the input possesses a minimal persistence-of-excitation order. No other special conditions are imposed on the kernel transfer functions or on the input signal, which may be deterministic or random with unknown statistics. The proposed algorithms are corroborated with simulation examples     

Second-order blind separation of sources based on canonical partialinnovations

This paper is devoted to the study of the second-order properties using partial autocorrelations of an instantaneous mixture of colored sources without additive noise. We introduce the notion of symmetric recursive canonical partial innovation. Then, their components, for the observation process, meet exactly with those of the source process from the order for which the autoregressive models underlying the sources are distinct. This property leads to a new separation method based on the sample counterpart of partial autocorrelation matrices associated with these innovations. Simulation results show a notable improvement of the achievements of such an approach with respect to those of similar methods. Two other separation methods related to partial autocorrelation are also discussed     

Stability in contractive nonlinear neural networks

We consider models of the form mu chi = -x + p + WF(x) where x = x(t) is a vector whose entries represent the electrical activities in the units of a neural network. W is a matrix of synaptic weights, F is a nonlinear function, and p is a vector (constant or slowly varying over time) of inputs to the units. If the map WF(x) is a contraction, then the system has a unique equilibrium which is globally asymptotically stable; consequently the network acts as a stable encoder in that its steady-state response to an input is independent of the initial state of the network. We consider some relatively mild restrictions on W and F(x), involving the eigenvalues of W and the derivative of F, that are sufficient to ensure that WF(x) is a contraction. We show that in the linear case with spatially-homogeneous synaptic weight, the eigenvalues of W are simply related to the Fourier transform of the connection pattern. This relation makes it possible, given cortical activity patterns as measured by autoradiographic labeling, to construct a pattern of synaptic weights which produces steady state patterns showing similar frequency characteristics. Finally, we consider the relationships, in the spatial and frequency domains, between the equilibrium of the model and that of the linear approximation mu chi = -x + p + Wx; this latter equilibrium can be computed easily from p in the homogeneous case using discrete Fourier transforms.     

A sinusoidal contrast function for the blind separation of statistically independent sources

The authors propose a new solution to the blind separation of sources (BSS) based on statistical independence. In the two-dimensional (2-D) case, we prove that, under the whiteness constraint, the fourth-order moment-based approximation of the marginal entropy (ME) cost function yields a sinusoidal objective function. Therefore, we can minimize it by simply estimating its phase. We prove that this estimator is consistent for any source distribution. In addition, such results are useful for interpreting other algorithms such as the cumulant-based independent component analysis (CuBICA) and the weighted approximate maximum likelihood (WAML) [or weighted estimator (WE)]. Based on the WAML, we provide a general unifying form for several previous approximations to the ME contrast. The bias and the variance of this estimator have been included. Finally, simulations illustrate the good consistency, convergence, and accuracy of the proposed method.     

Stability of differential multipass processes

Edwards' (1974) notion of stability along the pass for differential multipass processes is shown to be equivalent to what is known as pointwise asymptotic stability for delay differential systems     

Stability of the asymmetric nonlinear mode trapped in symmetricplanar waveguides

The authors examine the reliability of the numerical approach for studying the asymmetric nonlinear mode trapped in a thin linear film sandwiched in an infinite self-focusing medium, and thus resolve a controversy in the literature on the stability of the mode trapped between the bifurcation point and the transition point on the dispersion curve reported. They demonstrate that as a result of the instability there exists a class of quasi-periodic solutions arising from the instability in the asymmetric mode on the unstable branch and weakly stable branch. In addition, the effect of loss on the propagation characteristics of the nonlinear mode is investigated. The evolution is shown to follow the dispersion curve adiabatically in the stable region provided the loss is small, whereas the initial excitation on the unstable branch leads to evolution away from oscillation around the dispersion curve     

Fourth-order blind identification of underdetermined mixtures of sources (FOBIUM)

For about two decades, numerous methods have been developed to blindly identify overdetermined (P/spl les/N) mixtures of P statistically independent narrowband (NB) sources received by an array of N sensors. These methods exploit the information contained in the second-order (SO), the fourth-order (FO) or both the SO and FO statistics of the data. However, in practical situations, the probability of receiving more sources than sensors increases with the reception bandwidth and the use of blind identification (BI) methods able to process underdetermined mixtures of sources, for which P>N may be required. Although such methods have been developed over the past few years, they all present serious limitations in practical situations related to the radiocommunications context. For this reason, the purpose of this paper is to propose a new attractive BI method, exploiting the information contained in the FO data statistics only, that is able to process underdetermined mixtures of sources without the main limitations of the existing methods, provided that the sources have different trispectrum and nonzero kurtosis with the same sign. A new performance criterion that is able to quantify the identification quality of a given source and allowing the quantitative comparison of two BI methods for each source, is also proposed in the paper. Finally, an application of the proposed method is presented through the introduction of a powerful direction-finding method built from the blindly identified mixture matrix.     

Stability of certain time-varying nonlinear systems

A sufficient condition for the feedback stability of the cascade of a nonlinear element and a nonlinear element with positive impulse response is given.     

Optical bistability and instability in a semiconductor in the case where the relaxation time of free charge carriers and their equilibrium concentration are temperature-dependent

The influence of temperature dependences of the relaxation time of free carriers and their equilibrium concentration on the feasibility of the bistability and instability of steady states is considered. A model describing the process of interaction of optical radiation with a semiconductor was used in the consideration, with various assumptions concerning the conditions of this interaction made.     

Neural network approach to blind signal separation of mono-nonlinearly mixed sources

A new result is developed for separating nonlinearly mixed signals in which the nonlinearity is characterized by a class of strictly monotonic continuously differentiable functions. The structure of the blind inverse system is explicitly derived within the framework of maximum likelihood estimation and the system culminates to a special architecture of the 3-layer perceptron neural network where the parameters in the first layer are inversely related to the output layer. The proposed approach exploits both the structural and signal constraints to search for the solution and assumes that the cumulants of the source signals are known a priori. A novel statistical algorithm based on the hybridization of the generalized gradient algorithm and metropolis algorithm has been derived for training the proposed perceptron which results in improved performance in terms of accuracy and convergence speed. Simulations and real-life experiment have also been conducted to verify the efficacy of the proposed scheme in separating the nonlinearly mixed signals.     

Direction finding of coherent sources with nonlinear arrays

This paper presents an approach to estimate the directions-of-arrival (DOAs) of narrowband coherent (completely corrected) signals by an arbitrary geometry sensor array. The concept of focussing matrices is introduced to estimate the outputs of a virtual uniform linear array from the outputs of the real array in order to use spatial smoothing techniques. Unlike the work presented in [5], the proposed approach avoids multiple singular value decomposition (SVD) computations in the various sectors because it is not necessary to divide the field of view of the array into sectors. Simulation results are given to support the approach.On leave from the Department of Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, People's Republic of China.     

低成本：FPGA厂商角逐的技术战场

FPGA和CPLD正在向高速、高密度、低功耗、低成本的趋势发展，并以这种优势进入原来固定结构定制芯片所服务的大批量、低成本应用市场中。有关专家预测，由于掩膜成本持续居高不下，估计有超过60％的ASIC设计至少要进行一次以上的重制，从而导致产品面市推迟、成本预算超支。今后FPGA将会在100万门至500万门范围的设计应用中占主导地位，将替代传统的ASIC以实现复杂的设计功能。     

Numerical solution of the equations of mathematical physics with nonlinear sources

A method is obtained for the numerical solution of the systems of diffusion, Schrödinger, and wave equations with nonlinear sources. This method, which has the second order with respect to the time step, uses the Fourier transform and does not impose fundamental restrictions on either the change from 1D media to media of larger dimensionality or the increase in the number of system equations. The method assumes simplified boundary conditions and is primarily developed for physical studies rather than for engineering calculations.     

Bayesian blind separation of generalized hyperbolic processes in noisy and underdeterminate mixtures

In this paper, we propose a Bayesian sampling solution to the noisy blind separation of generalized hyperbolic signals. Generalized hyperbolic models, introduced by Barndorff-Nielsen in 1977, represent a parametric family able to cover a wide range of real signal distributions. The alternative construction of these distributions as a normal mean variance (continuous) mixture leads to an efficient implementation of the Markov chain Monte Carlo method applied to source separation. The incomplete data structure of the generalized hyperbolic distribution is indeed compatible with the hidden variable nature of the source separation problem. Both overdeterminate and underdeterminate noisy mixtures are solved by the same algorithm without a prewhitening step. Our algorithm involves hyperparameters estimation as well. Therefore, it can be used, independently, to fitting the parameters of the generalized hyperbolic distribution to real data.     

Stability of a class of nonlinear systems

A graphical criterion for testing the absolute stability of a particular class of nonlinear systems is given. The system, which may involve a number of nonlinearities, is investigated using the Nyquist plot of its linear part.     

Adaptive blind channel equalisation in chaotic communications by using nonlinear prediction technique

In chaotic communications, an ideal channel is often assumed. In practice, channel distortion is inevitable. In particular, in wireless chaotic communications, the channel distortion may be serious and must be compensated. An adaptive blind equalisation algorithm is proposed. The aim of the algorithm is to recover the chaotic signal transmitted through a finite impulse response (FIR) channel. The inherent characteristic of the chaotic signal, that is the high sensitivity to initial conditions, is exploited to formulate the criterion used in deriving the algorithm. The analysis of stability of the proposed algorithm is also provided