Harmonic signal extraction from noisy chaotic interference based on synchrosqueezed wavelet transform

For the harmonic signal extraction from chaotic interference, a harmonic signal extraction method is proposed based on synchrosqueezed wavelet transform(SWT). First, the mixed signal of chaotic signal, harmonic signal, and noise is decomposed into a series of intrinsic mode-type functions by synchrosqueezed wavelet transform(SWT) then the instantaneous frequency of intrinsic mode-type functions is analyzed by using of Hilbert transform, and the harmonic extraction is realized. In experiments of harmonic signal extraction, the Duffing and Lorenz chaotic signals are selected as interference signal, and the mixed signal of chaotic signal and harmonic signal is added by Gauss white noises of different intensities.The experimental results show that when the white noise intensity is in a certain range, the extracting harmonic signals measured by the proposed SWT method have higher precision, the harmonic signal extraction effect is obviously superior to the classical empirical mode decomposition method.

Energy distribution and effective components analysis of 2^(n) sequence pseudo-random signal

In order to extract usable harmonics from real 2^(n) sequence pseudo-random data,a technical method is proposed.An equation for predicting the average amplitude of the main frequencies is proposed to guide the choice of signal type for different exploration tasks.By the threshold of the amplitude of the transmitted signal,a set of candidate frequencies are first selected.Then,by operating a spectrum envelope method at these candidate frequencies on received data,effective components in data are extracted.A frequency density calculation method is proposed based on a logical number summation method,to reasonably characterize the frequency density in different frequency bands.By applying this method to real data in Sichuan,China,with signal Type 13,75 effective components are extracted,including both main frequencies and harmonics.The result suggests that the number of effective frequencies in the 2^(n) sequence pseudo-random signal can be increased by extracting usable harmonics,without any additional fieldwork.

Modal recovery of sea-level variability in the South China Sea using merged altimeter data

Using 20 years （1993-2012） of merged data recorded by contemporary multi-altimeter missions, a variety of sea-level variability modes are recovered in the South China Sea employing three- dimensional harmonic extraction. In terms of the long-term variation, the South China Sea is estimated to have a rising sea-level linear trend of 5.39 mm/a over these 20 years. Among the modes extracted, the seven most statistically significant periodic or quasi-periodic modes are identified as principal modes. The geographical distributions of the magnitudes and phases of the modes are displayed. In terms of intra- annual and annual regimes, two principal modes with strict semiannual and annual periods are found, with the annual variability having the largest amplitudes among the seven modes. For interannual and decadal regimes, five principal modes at approximately 18, 21, 23, 28, and 112 months are found with the most mode- active region being to the east of Vietnam. For the phase distributions, a series of amphidromes are observed as twins, termed ＂amphidrome twins＂, comprising rotating dipole systems. The stability of periodic modes is investigated employing joint spatiotemporal analysis of latitude/longitude sections. Results show that all periodic modes are robust, revealing the richness and complexity of sea-level modes in the South China Sea.

Unvoiced/voiced classification and voiced harmonic parameters estimation using the third-order statistics

Unvoiced/voiced classification of speech is a challenging problem especially under conditions of low signal-to-noise ratio or the non-white-stationary noise environment. To solve this problem, an algorithm for speech classification, and a technique for the estimation of palrwise magnitude frequency in voiced speech am proposed. By using third order spectrum of speech signal to remove noise, in this algorithm the least spectrum difference to get refined pitch and the max harmonic number is given. And this algorithm utilizes spectral envelope to estimate signal-to-noise ratio of speech harmonics. Speech classification, voicing probability, and harmonic parameters of the voiced frame can be obtained. Simulation results indicate that the proposed algorithm, under complicated background noise, especially Gaussian noise, can effectively classify speech in high accuracy for voicing probability and the voiced parameters.

A computational model for assessment of speech intelligibility in informational masking

The existing auditory computational mod- els for evaluating speech intelligibility can only account for energetic masking, and the effect of informational masking is rarely described in these models. This study was aimed to make a computational model considering the mechanism of informational masking. Several psy- choacoustic experiments were conducted to test the ef- fect of informational masking on speech intelligibility by manipulating the number of masking talker, speech rate, and the similarity of F0 contour between target and masker. The results showed that the speech recep- tion threshold for the target increased as the F0 contours of the masker became more similar to that of the tar- get, suggesting that the difficulty in segregating the tar- get harmonics from the masker harmonics may underlie the informational masking effect. Based on these stud- ies, a new auditory computational model was made by inducing the auditory function of harmonic extraction to the traditional model of speech intelligibility index （SII）, named as harmonic extraction （HF） model. The predictions of the HF model are highly consistent with the experimental results.