Current Issue : October - December Volume : 2018 Issue Number : 4 Articles : 5 Articles
In order to solve the problem of detecting a BOC signal, which uses a long-period pseudo random sequence, an algorithm is\npresented based on quadrature channel correlation. The quadrature channel correlation method eliminates the autocorrelation\ncomponent of the carrier wave, allowing for the extraction of the absolute autocorrelation peaks of the BOC sequence. If the same\nlag difference and height difference exist for the adjacent peaks, the BOC signal can be detected effectively using a statistical analysis\nof themultiple autocorrelation peaks.Thesimulation results show that the interference of the carrier wave component is eliminated\nand the autocorrelation peaks of the BOC sequence are obtained effectively without demodulation.The BOC signal can be detected\neffectively when the SNR is greater than âË?â??12 dB.The detection ability can be improved further by increasing the number of sampling\npoints. The higher the ratio of the square wave subcarrier speed to the pseudo random sequence speed is, the greater the detection\nability is with a lower SNR.The algorithm presented in this paper is superior to the algorithm based on the spectral correlation....
The continuous generalized wavelet transform (GWT) which is regarded as a kind of time-linear canonical domain\n(LCD)-frequency representation has recently been proposed. Its constant-Q property can rectify the limitations of the\nwavelet transform (WT) and the linear canonical transform (LCT). However, the GWT is highly redundant in signal\nreconstruction. The discrete linear canonical wavelet transform (DLCWT) is proposed in this paper to solve this\nproblem. First, the continuous linear canonical wavelet transform (LCWT) is obtained with a modification of the GWT.\nThen, in order to eliminate the redundancy, two aspects of the DLCWT are considered: the multi-resolution\napproximation (MRA) associated with the LCT and the construction of orthogonal linear canonical wavelets. The\nnecessary and sufficient conditions pertaining to LCD are derived, under which the integer shifts of a chirp-modulated\nfunction form a Riesz basis or an orthonormal basis for a multi-resolution subspace. A fast algorithm that computes\nthe discrete orthogonal LCWT (DOLCWT) is proposed by exploiting two-channel conjugate orthogonal mirror filter\nbanks associated with the LCT. Finally, three potential applications are discussed, including shift sampling in\nmulti-resolution subspaces, denoising of non-stationary signals, and multi-focus image fusion. Simulations verify the\nvalidity of the proposed algorithms....
In acoustic multi-channel equalization techniques, such as complete multi-channel equalization based on the\nmultiple-input/output inverse theorem (MINT), relaxed multi-channel least-squares (RMCLS), and partial multi-channel\nequalization based on MINT (PMINT), the length of the reshaping filters is generally chosen such that perfect\ndereverberation can be achieved for perfectly estimated room impulse responses (RIRs). However, since in practice\nthe available RIRs typically differ from the true RIRs, this reshaping filter length may not be optimal. This paper\nprovides a mathematical analysis of the robustness increase of equalization techniques against RIR perturbations\nwhen using a shorter reshaping filter length than conventionally used. Based on the condition number of the\n(weighted) convolution matrix of the RIRs, a mathematical relationship between the reshaping filter length and the\nrobustness against RIR perturbations is established. It is shown that shorter reshaping filters than conventionally used\nyield a smaller condition number, i.e., a higher robustness against RIR perturbations. In addition, we propose an\nautomatic non-intrusive procedure for determining the reshaping filter length based on the L-curve. Simulation\nresults confirm that using a shorter reshaping filter length than conventionally used yields a significant increase in\nrobustness against RIR perturbations for MINT, RMCLS, and PMINT. Furthermore, it is shown that PMINT using an\noptimal intrusively determined reshaping filter length outperforms all other considered techniques. Finally, it is shown\nthat the automatic non-intrusively determined reshaping filter length in PMINT yields a similar performance as the\noptimal intrusively determined reshaping filter length....
In this paper, a dimensionality reduction method applied on facial expression recognition is investigated. An\nunsupervised learning framework, projective complex matrix factorization (proCMF), is introduced to project\nhigh-dimensional input facial images into a lower dimension subspace. The proCMF model is related to both the\nconventional projective nonnegative matrix factorization (proNMF) and the cosine dissimilarity metric in the simple\nmanner by transforming real data into the complex domain. A projective matrix is then found through solving an\nunconstraint complex optimization problem. The gradient descent method was utilized to optimize a complex cost\nfunction. Extensive experiments carried on the extended Cohn-Kanade and the JAFFE databases show that the proposed\nproCMF model provides even better performance than state-of-the-art methods for facial expression recognition...
Preamplifier circuit noise is of great importance in quartz enhanced photoacoustic\nspectroscopy (QEPAS) system. In this paper, several noise sources are evaluated and discussed in\ndetail. Based on the noise characteristics, the corresponding noise reduction method is proposed. In\naddition, a frequency locked technique is introduced to further optimize the QEPAS system noise and\nimprove signal, which achieves a better performance than the conventional frequency scan method.\nAs a result, the signal-to-noise ratio (SNR) could be increased 14 times by utilizing frequency locked\ntechnique and numerical averaging technique in the QEPAS system for water vapor detection....
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