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For paired carrier multiple access (PCMA) signals, a new single-channel blind separation on neural network was proposed. Firstly, the sample waveforms (three symbols) which contains different bit information are constructed, secondly, the time-frequency spectrum of each sample under the different influences of the trailing symbols is Intercepted, finally, the characteristic data of the spectrum as the input data, and the two-bit sequence in each sample as the output data to be trained, network trains these data repeatedly to complete the construction of separation model. The receiver carries on window truncation to the time-frequency spectrum of PCMA signal, neural network recognize the characteristic data of these spectrums to realizes the separation of bit sequences. Experimental results show that this algorithm has lower complexity than PSP algorithm, and the accuracy of it is close to PSP algorithm (L=5).

To overcome the performance degradation of conventional Chirp parameters estimation methods in underwater acoustic multipath channels, a novel parameters estimation method based on Fractional Fourier transform (FRFT) and Fourier transform (FFT) was proposed. Firstly, the Chirp rate was estimated by searching for the best degree of Chirp after Fractional Fourier transform. Secondly, the Chirp signal turned into a single-frequency signal by means of Chirp rate equalization. Finally, FFT was applied to estimate the initial frequency. The simulation experiment show that the proposed algorithm enhanced about 1dB RMSE performance on Chirp initial frequency compared with FRFT while the computational complexity is similar to FRFT.

Flood defence assets such as earth embankments comprise the vital part of linear flood defences in many countries including the UK and protect inland from flooding. The risks of flooding are likely to increase in the future due to increasing pressure on land use, increasing rainfall events and rising sea level caused by climate change also affect aging flood defence assets. Therefore, it is important that the flood defence assets are maintained at a high level of safety and serviceability. The high costs associated with preserving these deteriorating flood defence assets and the limited funds available for their maintenance require the development of systematic approaches to ensure the sustainable flood-risk management system. The integration of realistic deterioration measurement and reliabilitybased performance assessment techniques has tremendous potential for structural safety and economic feasibility of flood defence assets. Therefore, the need for reliability-based performance assessment is evident. However, investigations on time-dependent reliability analysis of flood defence assets are limited. This paper presents a novel approach for time-dependent reliability analysis of flood defence assets. In the analysis, time-dependent fragility curve is developed by using the state-based stochastic deterioration model. The applicability of the proposed approach is then demonstrated with a case study.