混沌理论在现代信道编码技术中的应用

混沌现象是一种在自然界和人类社会中存在的普遍现象.混沌运动的基本特征是运动轨道的不稳定性,表现为对初始条件的敏感依赖性,又称为蝴蝶效应.如何将混沌研究成果应用于其它领域已成为非线性科学发展的重要课题,本文探索了如何将混沌理论应用到信道编码研究中.由于交织器和校验矩阵分别对Turbo码和LDPC码的性能起着至关重要的作用,本文致力于交织器和校验矩阵的研究和设计.根据Henon混沌模型的内在随机性分别对Turbo码中的交织器和LDPC码中的校验矩阵提出了新的设计方法.仿真结果表明:与现有方法相比,基于混沌理论构造的交织器和校验矩阵可分别使Turbo码和LDPC码获得更高的增益,因而混沌方法可用于构造出好的Turbo码和LDPC码.     

卷积神经网络在气体泄漏超声识别中的应用

为了克服现有气体泄漏检测方法的不足,提出一种基于卷积神经网络的气体泄漏超声信号识别方法。在设计卷积神经网络网络结构时,通过多次预训练确定网络层数、卷积核数目和尺寸、全连接层神经元数目。同时,选择Inception模块平衡网络宽度和深度,防止过拟合的同时提高网络对尺度的适应性。通过输气管道泄漏实验平台模拟工况中常见的阀门泄漏和垫片泄漏,利用短时傅里叶变换进行时频图表征,在此基础上,建立二分类模型和不同泄漏类型的三分类模型。结果表明,相比二分类模型,不同泄漏类型的三分类模型识别准确率有所降低,添加Inception模块可以有效提高三分类模型的性能。     

CYCLIC AND NEGACYCLIC CODES OF LENGTH 2p^s OVER Fp^m ＋ uFp^m

In this article, we focus on cyclic and negacyclic codes of length 2p^s over the ring R = Fp^m ＋ uFp^m, where p is an odd prime. On the basis of the works of Dinh （in J.Algebra 324,940-950,2010）, we use the Chinese Remainder Theorem to establish the algebraic structure of cyclic and negacyclic codes of length 2p^s over the ring Fp^m ＋ uFp^m in terms of polynomial generators. Furthermore, we obtain the number of codewords in each of those cyclic and negacyclic codes.     

Erased-Chase decoding for RS-coded MPSK signaling over a Rayleigh fading channel

In this paper, a novel dual-metric, the maximum and minimum Squared Euclidean Distance Increment （SEDI） Brought by changing the hard decision symbol, is introduced to measure the reliability of the received M-ary Phase Shift Keying （MPSK） symbols over a Rayleigh fading channel. Based on the dual-metric, a Chase-type soft decoding algorithm, which is called erased-Chase algorithm, is developed for Reed-Solomon （RS） coded MPSK schemes. The proposed algorithm treats the unreliable symbols with small maximum SEDI as erasures, and tests the non-erased unreliable symbols with small minimum SEDI as the Chase-2 algorithm does. By introducing optimality test into the decoding procedure, much more reduction in the decoding complexity can be achieved. Simulation results of the RS（63, 42, 22）-coded 8-PSK scheme over a Rayleigh fading channel show that the proposed algorithm provides a very efficient tradeoff between the decoding complexity and the error performance. Finally, an adaptive scheme for the number of erasures is introduced into the decoding algorithm.     

Speaker Recognition Using Constrained Convolutional Neural Networks in Emotional Speech

Speaker recognition is an important classification task, which can be solved using several approaches. Although building a speaker recognition model on a closed set of speakers under neutral speaking conditions is a well-researched task and there are solutions that provide excellent performance, the classification accuracy of developed models significantly decreases when applying them to emotional speech or in the presence of interference. Furthermore, deep models may require a large number of parameters, so constrained solutions are desirable in order to implement them on edge devices in the Internet of Things systems for real-time detection. The aim of this paper is to propose a simple and constrained convolutional neural network for speaker recognition tasks and to examine its robustness for recognition in emotional speech conditions. We examine three quantization methods for developing a constrained network: floating-point eight format, ternary scalar quantization, and binary scalar quantization. The results are demonstrated on the recently recorded SEAC dataset.     

CT and MRI Medical Image Fusion Using Noise-Removal and Contrast Enhancement Scheme with Convolutional Neural Network

Medical image fusion (MIF) has received painstaking attention due to its diverse medical applications in response to accurately diagnosing clinical images. Numerous MIF methods have been proposed to date, but the fused image suffers from poor contrast, non-uniform illumination, noise presence, and improper fusion strategies, resulting in an inadequate sparse representation of significant features. This paper proposes the morphological preprocessing method to address the non-uniform illumination and noise by the bottom-hat–top-hat strategy. Then, grey-principal component analysis (grey-PCA) is used to transform RGB images into gray images that can preserve detailed features. After that, the local shift-invariant shearlet transform (LSIST) method decomposes the images into the low-pass (LP) and high-pass (HP) sub-bands, efficiently restoring all significant characteristics in various scales and directions. The HP sub-bands are fed to two branches of the Siamese convolutional neural network (CNN) by process of feature detection, initial segmentation, and consistency verification to effectively capture smooth edges, and textures. While the LP sub-bands are fused by employing local energy fusion using the averaging and selection mode to restore the energy information. The proposed method is validated by subjective and objective quality assessments. The subjective evaluation is conducted by a user case study in which twelve field specialists verified the superiority of the proposed method based on precise details, image contrast, noise in the fused image, and no loss of information. The supremacy of the proposed method is further justified by obtaining 0.6836 to 0.8794, 0.5234 to 0.6710, and 3.8501 to 8.7937 gain for QFAB, CRR, and AG and noise reduction from 0.3397 to 0.1209 over other methods for objective parameters.     

一种基于深度可分离卷积的轻量级人体关键点检测算法

针对网络模型执行过程耗时过长的问题,受到像素切割网络架构中的编解码结构启发,设计了一种高效的轻量级主干网络,使用深度可分离卷积作为基本的卷积模块,利用了多维自学习模块(Multidimensional Self-Learning Module, MSLM)对特征矩阵进行自适应的学习来增强有用信息权重,同时使用编解码结构对其主干结构进行效率上的优化,设计出了深度可分离网络(Codec Depth Separable Network, CSDNet),相比于MobileNet性能提升了72%,精度提升了5.2%。     

Computerprogramm zur interaktiven Auswertung von 15N-tracerkinetischen Stoffwechselexperimenten

The theoretical concept of the computer program is based on the compartment theory for the 3-pool model using single pulse administration of the tracer. The code estimates the model parameters by means of the non-linear method of least squares fit under steady state conditions. Furthermore the parameters of the protein metabolism are calculated. The program works interactively and allows reading and modifying the experimental ¹⁵N tracer data via terminal and controlling the program.     

圭亚那乔治敦某五星级酒店暖通设计

详细介绍圭亚那乔治敦某五星级酒店空调系统在负荷计算、设备选型、空调系统自控、防排烟设计、LEED认证等设计情况。     

Performance of degree distribution based HARQ scheme for LDPC-coded OFDM system

This article studies the degree distribution property of low density parity check (LDPC) codes by Gaussian approximation (GA) and presents an efficient hybrid automatic repeat quest (HARQ) scheme for LDPC-coded orthogonal frequency division multiplexing (OFDM) system. In the scheme, the important bits with large degrees have high retransmission priorities and are mapped to the sub-carriers with better channel quality indicator (CQI) levels in the OFDM system. The new scheme provides more protection to the bits with large degrees and thus contributes more to the decoding process by offering more transmission power. In this way the system performance would be improved. The statistics and simulation results also prove the new scheme.