A method of blind recognition of the coding parameters for binary Bose-Chaudhuri-Hocquenghem (BCH) codes is proposed in this paper. We consider an intelligent communication receiver which can blindly recognize the coding parameters of the received data stream. The only knowledge is that the stream is encoded using binary BCH codes, while the coding parameters are unknown. The problem can be addressed on the context of the non-cooperative communications or adaptive coding and modulations (ACM) for cognitive radio networks. The recognition processing includes two major procedures: code length estimation and generator polynomial reconstruction. A hard decision method has been proposed in a previous literature. In this paper we propose the recognition approach in soft decision situations with Binary-Phase-Shift-Key modulations and Additive-White-Gaussian-Noise (AWGN) channels. The code length is estimated by maximizing the root information dispersion entropy function. And then we search for the code roots to reconstruct the primitive and generator polynomials. By utilizing the soft output of the channel, the recognition performance is improved and the simulations show the efficiency of the proposed algorithm.

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A novel fault-tolerant control method based on the equivalent substitution of voltage space vector for cascaded H-bridge multilevel inverter with current-tracking is proposed in this paper. With this method, the fault effects on the voltage vector of each sector of the cascaded inverter is analyzed first. Then, an algorithm to substitute the voltage vector in fault state is developed. In the fault state, if the voltage vector selected by the original algorithm cannot be used normally, the redundant voltage vector with the position coincidence is preferentially selected for equivalent substitution. If there is no redundant coincidence vector, select the other vector whose position and effect are closest to it. Compared with the commonly used N + 1 redundancy method, this method does not require the spare cascaded units and can be applied to any class cascaded H-bridge multilevel inverter with current-tracking to improve its reliability. Finally, the effectiveness of the proposed method is validated by simulation and experiment results.

Applying the particle filter (PF) technique, this paper proposes a PF-based algorithm to blindly demodulate the chaotic direct sequence spread spectrum (CDS-SS) signals under the colored or non-Gaussian noises condition. To implement this algorithm, the PFs are modified by (i) the colored or non-Gaussian noises are formulated by autoregressive moving average (ARMA) models, and then the parameters that model the noises are included in the state vector; (ii) the range-differentiating factor is imported into the intruder's chaotic system equation. Since the range-differentiating factor is able to make the inevitable chaos fitting error advantageous based on the chaos fitting method, thus the CDS-SS signals can be demodulated according to the range of the estimated message. Simulations show that the proposed PF-based algorithm can obtain a good bit-error rate performance when extracting the original binary message from the CDS-SS signals without any knowledge of the transmitter's chaotic map, or initial value, even when colored or non-Gaussian noises exist.