An approach of point sources detection in X-ray astronomical image using support vector machine

Since most of energy sources in our Universe appear point-like structures,the study of point sources detection method on astronomical images has become significant.In this paper,a point sources detection approach on X-ray astronomical image was proposed.Firstly,a thresholding method was used to separate the background noises.Then,the peak detection method was taken to detect the positions of potential point sources.After that,we extracted spectrum features of point sources and backgrounds,and generated the classification model using the Support Vector Machine.Finally,the correct point sources were got after discarding of spurious detections with the classification model.Our approach was applied to the X-ray image of Galaxy NGC 4552.Compared with “wavdetect”,our approach has the same performance of accuracy with a detection error rate of 5%,but a higher efficiency

A novel L-vector representation and improved cosine distance kernel for Text-dependent Speaker Verification

A text-dependent i-vector extraction scheme and a lexicon-based binary vector (L-vector) representation are proposed to improve the performance of text-dependent speaker verification.An utterance used for enrollment or test is represented by these two vectors.An improved cosine distance kernel combining i-vector and L-vector is constructed to discriminate both speaker identity and lexical (or text) diversity with back-end support vector machine(SVM).Experiments are conducted on RSR 2015 Corpus part 1 and part 2.The results indicate that at most 30% improvement can be obtained compared with traditional i-vector baseline

The application of sparse linear prediction dictionary to compressive sensing in speech signals

Appling compressive sensing (CS),which theoretically guarantees that signal sampling and signal compression can be achieved simultaneously,into audio and speech signal processing is one of the most popular research topics in recent years.In this paper,K-SVD algorithm was employed to learn a sparse linear prediction dictionary regarding as the sparse basis of underlying speech signals.Compressed signals was obtained by applying random Gaussian matrix to sample original speech frames.Orthogonal matching pursuit (OMP) and compressive sampling matching pursuit (CoSaMP) were adopted to recovery original signals from compressed one.Numbers of experiments were carried out to investigate the impact of speech frames length,compression ratios,sparse basis and reconstruction algorithms on CS performance.Results show that sparse linear prediction dictionary can advance the performance of speech signals reconstruction compared with discrete cosine transform (DCT) matrix

Speech enhancement ini-vector speaker verification system

To solve the model-mismatch problem in text-independent speaker verification system when training environment differs from recognition environment,We propose a i-vector speaker verification system using speech enhancement in front-end preprocessing it can improve the system robustness to additive noise.To estimate the performance of different speech enhancement methods,we used NIST08 core test set in the experiment.Four speech enhancement methods,including wiener filtering,MMSE-LSA,traditional spectral subtraction and multi-band spectral subtraction,combining with IMCRA noise estimation,were evaluated in the speaker verification system based on i-vector.The result shows the proposed system with speech enhancement had some improvement in noise environment and that multi-band spectral subtraction method performed the best when SNR was relatively high and MMSE-LSA performed the best when SNR was low

A novel design on multi-layer satellite constellation network

With the increasing demand of space technology,the traditional single layer satellite constellation network is restricted in the development of future space technology because of its simple structure.For this reason,more and more researchers have carried out the research on the multi-layer satellite constellation network in recent years.This paper put forward a new GEO/MEO/LEO satellite constellation design based on the advantages of multi-layer satellite constellation to achieve full coverage of the earth with as little satellites as possible.It is more stereo than traditional style.Finally,we use STK and MATLAB to realize the digital simulation of this design.The rationality and effectiveness of this design are verified by comparison and analysis of the length of the satellite link,the communication pitch angle and azimuth angle