四种数字混沌扩频序列的平衡性分析

探讨了Chebyshev、改进型Logistic、Logistic和Tent四种典型混沌映射的映射参数与平衡性之间的关系,得出了混沌序列新的映射参数取值范围,为混沌扩频码的产生提供了依据;并通过四种混沌序列的平衡性曲线图和映射参数对混沌扩频通信系统的误码率影响曲线图,验证了新取值范围的正确性。仿真和分析表明：Chebyshev映射的平衡性最好。     

L-Thr-TPPMg电子结构及光谱性质的理论研究

采用密度泛函理论方法在B3LYP和混合基组(C、H原子采用6-31G(d);Mg、N、O采用6-311++G(2d,p))水平对含L-苏氨酸侧链的四苯基卟啉镁衍生物L-Thr-TPPMg的基态几何构型进行了优化,获得了稳定的分子构型。以获得的稳定构型为基础,在相同基组水平进行了红外吸收光谱研究;采用含时密度泛函理论方法,在相同基组水平进行了紫外吸收光谱和电子圆二色谱研究。理论研究发现:(1)L-苏氨酸的羧基氧原子与镁原子之间存在配位作用。(2)氮镁配位键、氧镁配位键的伸缩振动在IR谱中的1022 cm~(-1)、278 cm~(1)处呈现特征吸收峰。(3)理论UV谱存在Soret带和Q带吸收。Q带吸收峰主要由HOMO→LUMO的荷移跃迁贡献;Sorer带的吸收峰主要由HOMO-1→LUMO的荷移跃迁贡献。(4)Sorct区表现出分裂的ECD谱。第1 Cotton效应主要来源于分子由HOMO-1→LUMO的荷移跃迁;第2 Cotton效应主要由HOMO-1→LUMO+1的荷移跃迁贡献。上述跃迁均为π→π~*的荷移跃迁。     

GMW序列和Hyperoval序列的互相关性

在n为奇数的情形下,研究了（GMW）序列和Hyperoval序列及其某一采样序列间的互相关函数。研究表明：GMW序列和Hyperoval序列及其某一采样序列间的互相关函数都可转化为m-序列与其采样序列间的互相关函数。     

Silhouette-based human action recognition using sequences of key poses

In this paper, a human action recognition method is presented in which pose representation is based on the contour points of the human silhouette and actions are learned by making use of sequences of multi-view key poses. Our contribution is twofold. Firstly, our approach achieves state-of-the-art success rates without compromising the speed of the recognition process and therefore showing suitability for online recognition and real-time scenarios. Secondly, dissimilarities among different actors performing the same action are handled by taking into account variations in shape (shifting the test data to the known domain of key poses) and speed (considering inconsistent time scales in the classification). Experimental results on the publicly available Weizmann, MuHAVi and IXMAS datasets return high and stable success rates, achieving, to the best of our knowledge, the best rate so far on the MuHAVi Novel Actor test.     

Numerical integration in the reconstruction of cardiac action potentials using Hodgkin-Huxley-type models

A comparison between traditional numerical integration methods and a new hybrid integration method for the reconstruction of action potential activity is presented, using a mathematical model of the cardiac Purkinje fiber (MNT model). It is shown that the hybrid integration method reduces importantly the overall computation time required for solving the Hodgkin-Huxley differential equations describing membrane electrical events. To accomplish this, the particular form of the gating variable equations is exploited to reformulate the step-by-step computation. In this way, the time increment can be made much larger compared with traditional methods when the membrane potential changes slowly. A mathematical analysis of the hybrid integration method is presented also, together with a numerical verification of its performance both for the propagated and nonpropagated membrane action potential. It is shown that the local error, that is the error arising at each integration step, and the cumulative integration error are strictly controlled by the membrane potential offset. Using the MNT model, the nonpropagated cardiac Purkinje action potential can be reconstructed in real time with an accuracy of 1% for the potential and 5% for the time of occurrence of its main features. In reconstructing propagated events, the hybrid integration method allows computation time savings by a factor of 10 or more compared to accurate Runge-Kutta schemes.     

Modeling synaptic plasticity in conjuction with the timing of pre- and postsynaptic action potentials

We present a spiking neuron model that allows for an analytic calculation of the correlations between pre- and postsynaptic spikes. The neuron model is a generalization of the integrate-and-fire model and equipped with a probabilistic spike-triggering mechanism. We show that under certain biologically plausible conditions, pre- and postsynaptic spike trains can be described simultaneously as an inhomogeneous Poisson process. Inspired by experimental findings, we develop a model for synaptic long-term plasticity that relies on the relative timing of pre- and post-synaptic action potentials. Being given an input statistics, we compute the stationary synaptic weights that result from the temporal correlations between the pre- and postsynaptic spikes. By means of both analytic calculations and computer simulations, we show that such a mechanism of synaptic plasticity is able to strengthen those input synapses that convey precisely timed spikes at the expense of synapses that deliver spikes with a broad temporal distribution. This may be of vital importance for any kind of information processing based on spiking neurons and temporal coding.     

Assessment of the maximum frequency components and digital sampling of cardiac Purkinje fiber action potentials

An investigation was made into a reasonable continuous sampling frequency for cardiac Purkinje fiber action potentials. Under the assumption that digital sampling will effectively capture frequency components up to half the sampling rate, action potential records made at 25 kHz were low-pass filtered at various cutoff frequencies. The filtered and unfiltered records were compared by calculating Vmax to determine the effects of progressive loss of high frequency components. It was determined that sampling at 13 kHz is adequate for action potentials with upstroke velocities up to 500 V/sec, and that estimation of Vmax in excess of 800 V/sec is possible.     

利用神经网络盲估计混沌直扩信号扩频序列*

混沌扩频序列具有比传统直扩序列更高复杂度的特点,然而它也同时是盲估计混沌直扩序列的难点。利用神经网络能无限任意逼近非线性函数的特点,设计了一种改进型的基于神经网络盲估计混沌扩频序列的方法。仿真结果表明,该方法无需搜索信息码和扩频序列之间的同步点,即使是在较低信噪比的条件下,仍然能有效的从噪声背景中盲分离出混沌扩频信号,并且盲估计出原始混沌序列。     

动态频谱抗干扰系统中跳频序列研究

现有的跳频序列,由于综合性能不均衡,参数无法实时改变,无法直接应用于动态频谱抗干扰系统中,因此迫切需要研究一种适用于动态频谱抗干扰系统的动态跳频序列。基于m伪随机序列,提出了一种频率数可根据通信环境实时变化的跳频序列。仿真结果表明,与基于固定参数的频率自适应跳频序列相比,动态跳频序列在均匀性、随机性、汉明相关性等方面均具有更好的性能。     

A review of methods for spike sorting: the detection and classification of neural action potentials

The detection of neural spike activity is a technical challenge that is a prerequisite for studying many types of brain function. Measuring the activity of individual neurons accurately can be difficult due to large amounts of background noise and the difficulty in distinguishing the action potentials of one neuron from those of others in the local area. This article reviews algorithms and methods for detecting and classifying action potentials, a problem commonly referred to as spike sorting. The article first discusses the challenges of measuring neural activity and the basic issues of signal detection and classification. It reviews and illustrates algorithms and techniques that have been applied to many of the problems in spike sorting and discusses the advantages and limitations of each and the applicability of these methods for different types of experimental demands. The article is written both for the physiologist wanting to use simple methods that will improve experimental yield and minimize the selection biases of traditional techniques and for those who want to apply or extend more sophisticated algorithms to meet new experimental challenges.     

2n周期二元序列的2位置错误谱

K错线性复杂度描述了k个位置发生变化后序列的线性复杂度的最小值,反映了序列的稳定性.但k错线性复杂度不能全面反映序列的稳定性,所以对k位置错误谱进行了研究,加深对k错线性复杂度的理解,更好得反映序列的稳定性.一般认为k错线性复杂度低的序列是不稳定的,不适合作为密钥序列,但是有的序列只有在改变某些位置才会引起线性复杂度的下降,k位置错误谱描述了错误位置的不同对线性复杂度的影响.主要是研究周期为2n的二元序列,发现这类序列线性复杂度的2位置错误谱的一些特征.     

Human action recognition using shape and CLG-motion flow from multi-view image sequences

In this paper, we present a method for human action recognition from multi-view image sequences that uses the combined motion and shape flow information with variability consideration. A combined local–global (CLG) optic flow is used to extract motion flow feature and invariant moments with flow deviations are used to extract the global shape flow feature from the image sequences. In our approach, human action is represented as a set of multidimensional CLG optic flow and shape flow feature vectors in the spatial–temporal action boundary. Actions are modeled by using a set of multidimensional HMMs for multiple views using the combined features, which enforce robust view-invariant operation. We recognize different human actions in daily life successfully in the indoor and outdoor environment using the maximum likelihood estimation approach. The results suggest robustness of the proposed method with respect to multiple views action recognition, scale and phase variations, and invariant analysis of silhouettes.     

Formation of pseudorandom sequences with improved autocorrelation properties

An original technique is proposed for formation of pseudorandom sequences on the basis of coding methods. The synthesis of large ensembles of signals with improved autocorrelation properties is theoretically substantiated. Methods of correlation analysis are used to study auto-and crosscorrelation properties of sequences being formed. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 3–16, January–February 2007.     

一种新的混沌扩频序列及其性能分析

结合传统的混沌映射,提出一种组合式混沌映射模型。给出了产生新的混沌扩频序列的方法。首先由给定初值代入组合式混沌映射进行迭代,并且通过随机的参数切换选择不同的组合混沌映射,再将迭代产生的序列进行预处理,最后将预处理后的序列进行L比特选择得到新的混沌扩频序列。对得到的混沌扩频序列进行平衡性、保密性和相关性分析,并与现有的混沌扩频序列的性能进行比较。结果表明,该混沌扩频序列具有与现有的混沌扩频序列相近的相关性,而且其平衡性、保密性更好。     

Statistical properties of finite sequences with high Kolmogorov complexity

We investigate to what extent finite binary sequences with high Kolmogorov complexity are normal (all blocks of equal length occur equally frequently), and the maximal length of all-zero or all-one runs which occur with certainty.Ming Li was supported by NSERC Operating Grant OGP-046506. Paul Vitányi was partially supported by NSERC International Scientific Exchange Award ISE0046203 and by the NWO through NFI Project ALADDIN under Contract Number NF 62-376.     

Sampling properties of the alternating projection distance geometry algorithm applied to unconstrained polypeptide chains

A comparison of the sampling properties of the alternating projection algorithm (APA) with those of other distance geometry algorithms for poly-L-alanine conformations is presented. The effects of several additions and modifications to the algorithm and the input data are studied. These include a parameter that controls the compactness of conformations and metrization, which chooses initial distances that satisfy the triangle inequalities. The effect of adding short-range distance bounds implied by steric interactions is also investigated. We find that with metrization our algorithm has similar sampling properties to the DISGEO program, as measured by mean square end-to-end distance, RMS coordinate deviation, and dihedral angle deviation. As an alternative to metrization, the compactness parameter can be used to sample conformations in a desired compactness range. We also find that improving short-range bounds leads to improved local geometry in the computed conformations with no additional computational cost. In appendices we show that the rms coordinate deviation is a metric on the set of equivalence classes of coordinate matrices varying by a rotation, and we present our pseudo code to compute random column metrization in O(n³) flops.