Gender blind? Australian immigration policy and practice, 1901-1930

This paper seeks to explore the nature of Australian immigration policies and practices, particularly their impact on women, from federation in 1901 to the cessation of large-scale assisted immigration to Australia brought about by the 1930s depression. The characteristics that influenced and affected female immigrants may have differentiated their experiences from those of male immigrants in the same period. Differential treatment of men and women has often been an unstated given in the formulation and implementation of immigration policies. It was as common to non-government organisations (of which there were, and still are, a great many associated with immigration and settlement), as to governments, both federal and state. Several inequities can be identified in the making and implementation of immigration and settlement policies, and in the access to government grants, concessions and services, not only in terms of race, ethnicity, class or occupation (which is well trodden ground in this field) but also in terms of gender.[1] Such differentiation is part of the broader framework of changing conceptions about the place and roles of women in Australian society and their expected contribution to the nation, but it has remained largely unexplicated in this period and field.

A new second-order method for blind signal separation from dynamic mixtures

This paper presents a new approach to separate colored stationary signals mixed by convolutive channels. A cost function is proposed by employing linear constraint to the demixing 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 source separation based on phase and frequency redundancy of cyclostationary signals

This paper presents a new method for blind source separation by exploiting phase and frequency redundancy of cyclostationary signals in a complementary way. It requires a weaker separation condition than those methods which only exploit the phase diversity or the frequency diversity of the source signals. The separation criterion is to diagonalize a polynomial matrix whose coefficient matrices consist of the correlation and cyclic correlation matrices, at time delay .TAU. = 0, of multiple measurements. An algorithm is proposed to perform the blind source separation. Computer simulation results illustrate the performance of the new algorithm in comparison with the existing ones.

Blind equalization of nonirreducible systems using the CM criterion

We address the blind equalization of finite-impulse-response (FIR) and multiple-input multiple-output (MIMO) channel systems excited by constant modulus (CM) signals. It is known that the algorithms based on the CM criterion can equalize an FIR MIMO system that is irreducible. The irreducible condition is restrictive as it requires all source signals to be received at sensors simultaneously. In this paper, we further show that the CM property of signals can be exploited to construct a zero-forcing equalizer for a system that is nonirreducible. Simulation examples demonstrate the proposed result.

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.

A modified CM algorithm for blind equalization of MPSK signals

A new blind equalization algorithm for application to wireless communication employing MPSK signals is proposed in this paper.  Since the new cost function exploits the amplitude and phase information simultaneously, the proposed algorithm can provide a superior performance than the conventional constant modulus algorithm (CMA) which only use the amplitude knowledge in its cost function.  Theoretical analysis and numerical simulations both demonstrate that the steady-state mean square error (MSE) for the proposed algorithm is less than that of the CMA.

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

Blind equalization of non-irreducible and non-column-reduced channels driven by constant modulus signals

We address the blind equalization of finite-impulse-response (FIR), multiple-input multiple-output (MIMO) channels excited by constant modulus (CM) signals. It is known that the algorithms based on the constant modulus (CM) criterion can equalize an FIR MIMO channel that is irreducible and column-reduced. We show in this paper that the CM property of signals can be exploited to construct a zero-forcing equalizer for a non-irreducible and non-column-reduced channel. We also give a lower bound for the order of the equalizer. Simulation examples demonstrate the proposed result.

Adaptive blind channel equalization based on constellation information of MPSK signal

In this paper, we propose a new adaptive algorithm for the blind equalization of an FIR (finite impulse response) channel excited by an M-ary phase shift keying (MPSK) signal. Different from the conventional constant modulus algorithm (CMA), which exploits the amplitude information of the input signal, the proposed algorithm exploits the full constellation information of the input signal. Theoretical analysis shows that the new algorithm has less mean square error (MSE), namely better equalization performance, in steady state than the CMA. Numerical simulations show the effectiveness of the new algorithm

Blind equalization of non-irreducible channels driven by MPSK signals

This paper deals with the problem of blind equalization of finite-impulse-response (FIR) and multiple-input multiple-output (MIMO) channels excited by M-ary phase shift keying (MPSK) signals. It is known that the algorithms based on the constant modulus (CM) criterion can equalize an FIR MIMO channel that is irreducible. The irreducible condition is restrictive since it requires that all source signals arrive at the receiving antennas simultaneously. In this paper, we show that the CM criterion can also be used to construct a zero-forcing equalizer for a channel that is non-irreducible. We also derive a lower bound for the order of the equalizer. The proposed result is validated by numerical simulations.

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.

A new algorithm for blind separation of cyclostationary source from linear mixtures

This paper addresses the problem of separating a cyclostationary source from linear mixtures. It first shows that if the cyclic frequencies of the source of interest are known and different from those of the interfering sources, perfect source separation can be achieved using the proposed separation criterion. Then an algorithm is derived to perform the blind source separation. Simulation results demonstrate the validity of the proposed algorithm