单片机在水声通讯中的应用

文章以水声通讯设备改进、提高为实例 ,介绍了单片机在该类设备中的具体应用。并重点阐述了在软件编程中判码方法等关键技术。

Discriminant Classification Model of DNA Sequence

[Objective] The research aimed to construct the discriminant classification model of DNA sequence by combining with the biology knowledge and the mathematical method.[Method] According to the polarity nature of side chain radical in the amino acid,the classification information of amino acid which represented the sequence characteristic from the content and array situation of base was extracted from the different sequences that the amino acid content was different.The four-dimension vector was used to represent.Mahalanobis distance and Fisher discriminant methods were used to classify the given sequence.[Result] In the model,the back substitution rates of sample obtained by two kinds of classification methods were both 100%,and the consistent rate of classification was 90%.[Conclusion] In the model,the calculation method was simple,and the accuracy of classification result was higher.It was superior to the discriminant classification model which was only based on the base content.

Learning compact binary code based on multiple heterogeneous features

A novel hashing method based on multiple heterogeneous features is proposed to improve the accuracy of the image retrieval system. First, it leverages the imbalanced distribution of the similar and dissimilar samples in the feature space to boost the performance of each weak classifier in the asymmetric boosting framework. Then, the weak classifier based on a novel linear discriminate analysis （LDA） algorithm which is learned from the subspace of heterogeneous features is integrated into the framework. Finally, the proposed method deals with each bit of the code sequentially, which utilizes the samples misclassified in each round in order to learn compact and balanced code. The heterogeneous information from different modalities can be effectively complementary to each other, which leads to much higher performance. The experimental results based on the two public benchmarks demonstrate that this method is superior to many of the state- of-the-art methods. In conclusion, the performance of the retrieval system can be improved with the help of multiple heterogeneous features and the compact hash codes which can be learned by the imbalanced learning method.

Soft Decoding Scheme of Convolution Code Combined with Huffman Coding

This paper proposes a modification of the soft output Viterbi decoding algorithm (SOVA) which combines convolution code with Huffman coding. The idea is to extract the bit probability information from the Huffman coding and use it to compute the a priori source information which can be used when the channel environment is bad. The suggested scheme does not require changes on the transmitter side. Compared with separate decoding systems, the gain in signal to noise ratio is about 0 5-1.0 dB with a limi...

运动数据中的最优关联数据的分类分析

针对传统关联数据分类方法一直存在分类精度差的问题,提出一种运动数据中的最优关联数据的分类方法。由于运动数据的变化量十分的庞大,同时变化程度也无法用规律进行推导,因此需要确定运动数据中的最优关联数据,通过最优关联数据的关联性进行高速提取,使用异导函数对提取的数据进行系统的分类。为了保证提出的运动数据中的最优关联数据的分类方法的有效性,设计对比仿真实验,通过实验数据表明,提出的运动数据中的最优关联数据的分类方法能够准确地对运动数据中的最优关联数据进行系统分类。

Faster-than- Nyquist rate communication via convolutional neural networks- based demodulators

A demodulator based on convolutional neural networks（ CNNs） is proposed to demodulate bipolar extended binary phase shifting keying（ EBPSK） signals transmitted at a faster-thanNyquist（ FTN） rate, solving the problem of severe inter symbol interference（ ISI） caused by FTN rate signals. With the characteristics of local connectivity, pooling and weight sharing,a six-layer CNNs structure is used to demodulate and eliminate ISI. The results showthat with the symbol rate of 1. 07 k Bd, the bandwidth of the band-pass filter（ BPF） in a transmitter of 1 k Hz and the changing number of carrier cycles in a symbol K = 5,10,15,28, the overall bit error ratio（ BER） performance of CNNs with single-symbol decision is superior to that with a doublesymbol united-decision. In addition, the BER performance of single-symbol decision is approximately 0. 5 d B better than that of the coherent demodulator while K equals the total number of carrier circles in a symbol, i. e., K = N = 28. With the symbol rate of 1. 07 k Bd, the bandwidth of BPF in a transmitter of 500 Hz and K = 5,10,15,28, the overall BER performance of CNNs with double-symbol united-decision is superior to those with single-symbol decision. Moreover, the double-symbol uniteddecision method is approximately 0. 5 to 1. 5 d B better than that of the coherent demodulator while K = N = 28. The demodulators based on CNNs successfully solve the serious ISI problems generated during the transmission of FTN rate bipolar EBPSK signals, which is beneficial for the improvement of spectrum efficiency.

ACTIVITY ATTACK ON REDUCED VARIANTS OF RIJNDAEL

The famous Square attacks against the Rijndael algorithm have taken advantage of the change of the balance of some bytes. Further study shows that the change of activity always happens before the change of balance, which builds the foundation for a new activity attack presented in this paper. In the activity attack, the round in which the activity changes is executed in an equivalent form to avoid the obstructive restriction of the subkeys of that round.The existence of the birthday paradox guarantees much fewer plaintexts necessary for activity attacks comparing with that for corresponding Square attacks. But no benefit may result from the new attacks performed independently because the activity attacks guess four instead of one key byte once. Only when both the balance property and the activity property are exploited at the same time can much better performance be obtained. The better performance in the simulation shows that the consuming time and chosen plaintexts necessary are both reduced to one tenth of those of the corresponding Square attacks. So the activity attacks could be viewed as an efficient supplement to the Square attacks.

Cooperative DVB-SH Satellite Broadcasting Systems with Rotated Signal Constellations

In this paper,we study the advantages of cooperation in broadcasting systems from a geosynchronous earth orbit(GEO)satellite to mobile terminals(MTs),achieved through a terrestrial complementary ground station(CGS) with fixed installment,which acts as a relay.Moreover and in the context of the digital video broadcasting-satellite-to-handheld(DVB-SH) standard,the performance improvements offered by the rotated constellations method are investigated,where prior transmission,a phase rotation of the transmitted symbols by a fixed angle is applied followed by a random component interleaver.Turbo codes with soft decision decoding and appropriate random channel interleavers are also considered.We present analytical expressions for the bit log-likelihood ratios(LLRs)that are needed for soft decision decoding at the MT turbo decoder,while the code combining technique is adapted to improve the end-to-end(E2E) performance.Then,we obtain through extensive computer simulations the average bit error probability(ABEP) of quadrature phase-shift keying(QPSK) signals received over pure land-mobile satellite(LMS)and pure CGS links for coding rates 1/3 and6/7.Moreover,the optimal rotation angles are obtained for both links.E2 E ABEP results are then presented assuming cooperation between GEO and CGS,while the power allocation issue is investigated under fixed total transmission power.Our performance evaluation results show that by using the constellation rotation technique,a performance gain can be achieved for high coding rates.

Discriminative Structured Dictionary Learning for Image Classification

In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary's discriminative power, the reconstruction error, classification error and inhomogeneous representation error are integrated into the objective function. The proposed approach learns a single structured dictionary and a linear classifier jointly. The learned dictionary encourages the samples from the same class to have similar sparse codes, and the samples from different classes to have dissimilar sparse codes. The solution to the objective function is achieved by employing a feature-sign search algorithm and Lagrange dual method. Experimental results on three public databases demonstrate that the proposed approach outperforms several recently proposed dictionary learning techniques for classification.

Using long-range contact number information for protein secondary structure prediction

In this paper, we first combine tetra-peptide structural words with contact number for protein secondary structure prediction. We used the method of increment of diversity combined with quadratic discriminant analysis to predict the structure of central residue for a sequence fragment. The method is used tetra-peptide structural words and long- range contact number as information resources. The accuracy of Q3 is over 83% in 194 proteins. The accuracies of predicted secondary structures for 20 amino acid residues are ranged from 81% to 88%. Moreover, we have introduced the residue long-range contact, which directly indicates the separation of contacting residue in terms of the position in the sequence, and examined the negative influence of long-range residue interactions on predicting secondary structure in a protein. The method is also compared with existing prediction methods. The results show that our method is more effective in protein secondary structures prediction.