A preliminary investigation of the relationship between parental empathy and social anxiety and children's social anxiety

This study investigated the association between parents' social anxiety and empathy, and their children's social anxiety, Twenty-one mothers, 12 fathers and 24 children aged between 7 and 12 years were recruited from state primary schools in the eastern metropolitan region of Melbourne, Australia. Parents completed self-report questionnaires assessing their parental empathy and level of social anxiety. Children completed a modified version of the social anxiety questionnaire. All parent variables, except for maternal anxiety, were related to children's social anxiety. Overall, parental empathy was found to have a considerable association with child social anxiety, which is consistent with arguments that micro-level family mechanisms are important influences on child social anxiety. Future studies of parental empathy with clinical populations and data collection from multiple sources are recommended.

A new second order method for blind signal separation from convolutive mixtures

This paper presents a new approach to separate colored signals mixed by FIR (finite impulse response) and MIMO (multiple-input multiple-output) channels. A cost function is proposed by employing linear constrainit to the de mixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.

Blind separation of cyclostationary sources based on phase-frequency redundancy

Thin paper presents a new algorithm for blind source separation (BSS) by exploiting phase and frequency redundancy of cyclostationary signals in a complementary way. The separation criterion is to diagonalize a polynomial matrix whose coefficient matrices consist of the correlation and cyclic correlation matrices of multiple measurements. Computer simulation results illustrate, the performance of the new algorithm in comparison with some existing algorithms.

Blind separation of cyclostationary signals from instantaneous mixtures

This paper presents a new approach for blind separation of unknown cyclostationary signals from instantaneous mixtures. The proposed method can perfectly separate the mixed source signals so long as they have either different cyclic frequencies or clock phases. This is a weaker condition than those required by the algorithms. The separation criterion is to diagonalize a polynomial matrix whose coefficient matrices consist of the correlation and cyclic correlation matrices, at time delay τ=0, of multiple measurements.

Adaptive blind source separation using constant modulus criterion and signal mutual information

We address the problem of adaptive blind source separation (BSS) from instantaneous multi-input multi-output (MIMO) channels. It is known that the constant modulus (CM) criterion can be used to extract unknown source signals. However, the existing CM based algorithms normally extract the source signals in a serial manner. Consequently, the accuracy in extracting each source signal, except for the first one, depends on the accuracy of previous source extraction. This estimation error propagation (accumulation) causes severe performance degradation. In this paper, we propose a new adaptive separation algorithm that can separate all source signals simultaneously by directly updating the separation matrix. The superior performance of the new algorithm is demonstrated by simulation examples

A new blind signal separation algorithm for instantaneous MIMO system

We address the problem of adaptive blind source separation (BSS) from instantaneous multi-input multi-output (MIMO) channels. In this paper, we propose a new constant modulus (CM)-based algorithm which employ nonlinear function as the de-correlation term. Moreover, it is shown by theoretical analysis that the proposed algorithm has less mean square error (MSE), i.e., better separation performance, in steady state than the cross-correlation and constant modulus algorithm (CC-CMA). Numerical simulations show the effectiveness of the proposed result.