This paper proposes a method of improving demodulation performance for chaotic synchronization based multiplex communications systems. In a conventional system, the number of data demodulated correctly is limited because transmitted chaotic signals interfere with each other. The proposed system uses a generalized inverse of a matrix formed from chaotic signals at the transmitter. Since this completely cancels the interference between chaotic signals, demodulation performance is greatly improved. The proposed system has the following features: A simple correlation receiver suitable for small terminals can be used; The magnitude of the correlator output is constant for binary data transmission; Analog information data can also be transmitted. Two methods to reduce the peak-to-average power ratio of the transmitted signal are presented.

In this letter, we propose a blind adaptive receiver with nonlinear structure for DS/CDMA communication systems. The proposed receiver requires the signature waveform and timing for only the desired user. It is shown that the blind adaptation is equivalent to the adaptation with the training signal and the function to be minimized has no local minima.

In this paper, three issues concerning the linear adaptive receiver using the LMS algorithm for single-user demodulation in direct-sequence/code-division multiple-access (DS/CDMA) systems are considered. First, the convergence rate of the LMS algorithm in DS/CDMA environment is considered theoretically. Both upper and lower bounds of the eigenvalue spread of the autocorrelation matrix of receiver input signals are derived. It is cleared from the results that the convergence rate of the LMS algorithm becomes slow when the signal power of interferer is large. Second, fast converging technique using a prefilter is considered. The LMS based adaptive receiver using an adaptive prefilter adjusted by a Hebbian learning algorithm to decorrelate the input signals is proposed. Computer simulation results show that the proposed receiver provides faster convergence than the LMS based receiver. Third, the complexity reduction of the proposed receiver by prefiltering is considered. As for the reduced complexity receiver, it is shown that the performance degradation is little as compared with the full complexity receiver.

Stable phase locked states" are found amongst the equiliblia of the phasor model known as a generalized Hopfield model having complex-valued local states on the unit circle with centre at the origin. The asynchronous updating rule is assumed, and the energy decreasing characteristic is used to investigate a property of the equilibrium states. Some of the equilibria are shown to be fragile" in the sense that the energy is not locally convex. It is also shown that the local convexity of the energy is assured by a sort of consistency between the equilibrium and the connection weights.

A new phasor model of neural networks is proposed in which the state of each neuron possibly takes the value at the origin as well as on the unit circle. A stability property of equilibria is studied in association with the energy landscape. It is shown that a simple condition guarantees an equilibrium to be asymptotically stable.