Applied Mechanics and Materials Vols. 556-562

Abstract: As a good time and frequency domain localization features, the method of wavelet ridge became one of effective ways to identify the pulse modulation. Aiming at the problem of the low intra pulse recognition rate of the wavelet ridge method in the situation of low signal-to-noise ratio, this paper presented a method of fast wavelet ridge intra pulse modulation based on singular value decomposition. The basic idea of this method:The first signal for fast Morlet wavelet transform; determined the singular value decomcomposition filtering threshold; According to the iterative method to extract the wavelet ridge was to calculate the instantaneous signal teristics; then to identify signal according to the different characteristics of signal instantaneous frequency. The simulation results show that: In less than or equal 0dB SNR situation, this method can improve the recognition rate of common pulse modulation.

Abstract: We use deep max-pooling convolutional neural networks to address a problem of neuroanatomy, namely, the automatic segmentation of cerebral cortex structures of laboratory rat depicted in stacks of Two-photon microscopy images and detect the change areas when stimulation occurs. We classify each pixel in the image by training a CNN network, using a square window to predict the probability of the central pixel for each class. After classification, we perform the post-processing on the output produced by CNN. At last, we depict the areas that we interested through a threshold value.

Abstract: The free space optical (FSO) system model is analyzed based on on-off keying (OOK), pulse position modulation (PPM), differential pulse position modulation (DPPM) and digital pulse interval modulation (DPIM) under the weak turbulence atmosphere. To improve the system performance, one effective way is to use forward error correction (FEC).The bit error rate (BER) calculating formula of uncoded system is derived under all above the modulations firstly, then as a benchmark, under the case of independent with identical distribution, the average bit error rates of RS coded system are derived, respectively. Simulations of the average bit error rate performance of these systems are done. Simulation results show that, PPM has the best bit error rate performance, RS coded is efficient to get the code gain and to improve jamming-rejection capability of system.

Abstract: For the purpose of improving adaptive performance of chaotic signals de-noising with wavelet transform, a method of Memetic-algorithm-based adaptive wavelet de-noising (MAWD) is presented. The MAWD based on generalized cross validation (GCV) is competent to obtain the global optimum thresholds and to raise the efficiency of adaptive searching computation. The de-noising results of simulative Lorenz time series are presented. The results show that the chaotic signals de-noised by MAWD can remove the white noise more effectively than the signals de-noised by using standard soft threshoding method (STM) and genetic-algorithm-based adaptive wavelet de-noising (GAWD), and the advantages are more apparent under the condition of lower SNR. The Lorenz time series with lower SNR de-noised by MAWD and GAWD respectively are predicted by Volterra adaptive filters, and the results show that the prediction absolute error of Lorenz time series de-noised by MAWD is nearly nine times smaller than that by GAWD. This method has a promising prospect in practical Chaotic signals de-noising.

Abstract: An improved algorithm of spacecraft signal combining for antenna array and its implementation are researched. Firstly the composition of the antenna array experiment system and the processing flow of the signal combining are introduced. Then the high-precision delay extracting technique in signal combing processing is researched. Finally a signal combining experiment on the data-transmission signal of Chang’E-2 spacecraft is conducted and a full spectrum software combining processer is specially designed for the antenna array system. The experiment results show that the combining efficiency can reach 88.1%.

Abstract: The traditional database information retrieval method is achieved by retrieving simple corresponding association of the attributes, which has the necessary requirement that image only have a single characteristic, with increasing complexity of image, it is difficult to process further feature extraction for the image, resulting in great increase of time consumed by large-scale image database retrieval. A fast retrieval method for large-scale image databases is proposed. Texture features are extracted in the database to support retrieval in database. Constraints matching method is introduced, in large-scale image database, referring to the texture features of image in the database to complete the target retrieval. The experimental results show that the proposed algorithm applied in the large-scale image database retrieval, augments retrieval speed, thereby improves the performance of large-scale image database.

Abstract: In online education, the three-dimensional image is transmitted remotely via the network, the amount of information contained in a three-dimensional image is higher than the two-dimensional pixel, reconstruction is also more complex than the two-dimensional, once interference is present, the three-dimensional features of image lost. To avoid these shortcomings, an anti-interference transmission method based on new remote image network is presented for online education. Image enhancement method is applied to strengthen the contents of the image, and support vector machine method is utilized to optimize the compression process of wavelet coefficients, and ensure low-loss compression. Experimental results show that the algorithm benefits remote network education in transmitting three-dimensional image to the terminal accurately and the image compression losses are reduced.

Abstract: In order for the effective recognition of face in the videos of complex environments, this paper presents an algorithm of face tracking of robust. Basing on the rigid constraints, this algorithm generates the potential rectangular area of face tracking,generates the isosceles triangle for the front–view images, generates the right angled triangle for the side images, and reaches the effective rate as 98.18% of face recognition in different sizes, lightings, poses,expressions and even under different noises.

Abstract: The signal obtained through measurement is inevitably with noise and interference. Traditional signal denoising method often takes the threshold way to process the wavelets or wavelet packets of noise signal for the purpose of denoising. Denoising by making use of slip threshold value of wavelet packets is proposed by this paper, to quantize the slip threshold value of wavelet packet decomposition coefficient, so as to obtain the reconstructed signal denoising. It is shown by the computer simulation results that the slip threshold value is with good practical value.

Abstract: Biological communication behavior is in everywhere, all over the nature, biological system and human society. In simple terms, Swarm intelligence is emerging though information communication and collaboration among some dispersed and simple individuals. Inspired by biological communication behavior, aimed at understanding swarm system collective dynamics behavior, and from the point of system cybernetics, this paper study the relevant biological communication dynamic model, such as the symbiotic model, attractive-repulsive model, external effect model and the multi-population coevolution model and so on. Also introduce the rules of these models, which provide theoretical basis for designing intelligent swarm intelligent system.