PSO并行优化LSSVR非线性黑箱模型辨识

针对非线性黑箱系统辨识中存在不确定性、高阶次,采用常规辨识方法建立其精确数学模型十分困难等问题,提出一种基于自适应粒子群算法的最小二乘支持向量机回归(PSO-LSSVR)非线性系统辨识方法.该方法采用2组自适应粒子群算法并行计算模型,分别利用自适应粒子群算法对LSSVR中的参数进行自动选取和矩阵迭代求解,既克服了传统LSSVR参数难以确定的缺点,提高了辨识精度,同时避免了复杂矩阵求逆运算,加快了计算速度.将该方法应用于船舶操纵性模型非线性系统辨识,仿真结果表明,由该方法得到的LSSVR能够有效地对系统进行建模,仿真精度高,结构简单,具有一定的理论推广意义.     

A Chinese liquor classification method based on liquid evaporation with one unmodulated metal oxide gas sensor

Electronic nose has been widely used in the classification of liquid samples, such as vinegars, wines and liquors, which have complex components. The difficulty of these classifications is how to get the information of the trace components in these samples. In this paper a method for liquor recognition based on liquid evaporation was presented. This method makes use of the distinct evaporation characteristics of different components in liquor samples. And during the evaporation process, one metal oxide gas sensor was used to detect the headspace of liquor samples for classification. Due to the distinct evaporation characteristics of different components, volatile compounds in the headspace evaporating from samples would change with the testing time. Meanwhile, the gas sensor would respond to these volatile compounds. Accordingly, more information of liquor samples during evaporation may be acquired with the proposed method. To verify the performance of this method, 8 different Chinese liquors with 50% alcohol for comparison were tested under the method. The results showed that the evaporation characteristics of these liquor samples were quite distinct. The correct classification accuracy of discriminant function analysis was 100%, which indicated this method may be a simple and effective way for complex-component liquid sample analysis.     

On the decoding of binary cyclic codes with the Newton identities

We revisit in this paper the concept of decoding binary cyclic codes with Gröbner bases. These ideas were first introduced by Cooper, then Chen, Reed, Helleseth and Truong, and eventually by Orsini and Sala. We discuss here another way of putting the decoding problem into equations: the Newton identities. Although these identities have been extensively used for decoding, the work was done manually, to provide formulas for the coefficients of the locator polynomial. This was achieved by Reed, Chen, Truong and others in a long series of papers, for decoding quadratic residue codes, on a case-by-case basis. It is tempting to automate these computations, using elimination theory and Gröbner bases.Thus, we study in this paper the properties of the system defined by the Newton identities, for decoding binary cyclic codes. This is done in two steps, first we prove some facts about the variety associated with this system, then we prove that the ideal itself contains relevant equations for decoding, which lead to formulas.Then we consider the so-called online Gröbner basis decoding, where the work of computing a Gröbner basis is done for each received word. It is much more efficient for practical purposes than preprocessing and substituting into the formulas. Finally, we conclude with some computational results, for codes of interesting length (about one hundred).     

Identification and quantification of different vapours using a single polymer chemoresistor and the novel dual transient temperature modulation technique

This paper presents a novel signal processing technique for a square wave temperature modulated carbon black/polymer composite sensor. The technique consists of only two mathematical operations: summing the off- and on-transients of the conductance signals, and subtracting the steady-state conductance signal. The technique has been verified through its application to a carbon black/polyvinylpyrrolidone composite chemoresistor. Identification of water, methanol and ethanol vapours was successfully demonstrated using the peak time of the resultant curves. Furthermore, quantification of those vapours was found to be possible using the height of the peak heights, which was linearly proportional to concentration. The technique does not require zero-gas calibration and thus is superior to previously reported techniques.     

Quadratic optimal neural fuzzy control for synchronization of uncertain chaotic systems

This paper presents a novel quadratic optimal neural fuzzy control for synchronization of uncertain chaotic systems via H^∞ approach. In the proposed algorithm, a self-constructing neural fuzzy network (SCNFN) is developed with both structure and parameter learning phases, so that the number of fuzzy rules and network parameters can be adaptively determined. Based on the SCNFN, an uncertainty observer is first introduced to watch compound system uncertainties. Subsequently, an optimal NFN-based controller is designed to overcome the effects of unstructured uncertainty and approximation error by integrating the NFN identifier, linear optimal control and H^∞ approach as a whole. The adaptive tuning laws of network parameters are derived in the sense of quadratic stability technique and Lyapunov synthesis approach to ensure the network convergence and H^∞ synchronization performance. The merits of the proposed control scheme are not only that the conservative estimation of NFN approximation error bound is avoided but also that a suitable-sized neural structure is found to sufficiently approximate the system uncertainties. Simulation results are provided to verify the effectiveness and robustness of the proposed control method.     

蒸发温度对电子鼻白酒评价的影响研究

采用气体传感器阵列对7种市售白酒进行了动态测量,并研究蒸发温度对白酒识别分类的影响.白酒样本分别在20,40,60,80℃蒸发后进行测量,在每个蒸发温度下结合主元分析(PCA)法,分析了传感器阵列信号与白酒的香型和酒精度特征之间的关系,以及所有白酒样本按蒸发温度划分的结果.结果表明:按香型和酒精度划分,60℃的分类结果...     

Limitations of nonlinear discrete periodic control for disturbance attenuation and robust stabilization

This paper presents a performance analysis of nonlinear periodically time-varying discrete controllers acting upon a linear time-invariant discrete plant. Time-invariant controllers are distinguished from strictly periodically time-varying controllers. For a given nonlinear periodic controller, a time-invariant controller is constructed. Necessary and sufficient conditions are given under which the time-invariant controller gives strictly better control performance than the time-invariant controller from which it was obtained, for the attenuation of l_p exogenous disturbances and the robust stabilization of l_p unstructured perturbations, for all p[1,∞].     

A method of predicting the number of clusters using Rand's statistic

Distributional and asymptotic results on the moment of Rand's C_k statistic were derived by DuBien and Warde [1981. Some distributional results concerning a comparative statistic used in cluster analysis. ASA Proceedings of the Social Statistics Section, 309–313.]. Based on those results, a method to predict the number of clusters is suggested by applying various agglomerative clustering algorithms. In the procedure, the methods using different indexes are examined and compared based on the concept of agreement (or, disagreement) between clusterings generated by different clustering algorithms on the set of data. Our method having practical generality works better than the other methods and assigns statistical meaning to C_k values in determining the number of clusters from the comparison.     

炭黑填充导电丁腈橡胶研究

研究了用华光化工厂产导电炭黑填充丁腈橡胶的导电性规律。探讨了配方、加工工艺、混炼胶存放、胶料老化以及测试条件等诸多因素与导电性的关系。优选出了硬度７０左右的胶料，其体积电阻率为２．２２Ω·ｃｍ。     

雨型对东北黑土区坡耕地土壤侵蚀影响的试验研究

降雨雨型对土壤侵蚀过程有重要的影响,也是当前土壤侵蚀研究的热点之一。通过野外原位人工模拟降雨试验,设计了次降雨中平均降雨强度、总降雨量相同的4种不同降雨雨型(均匀型:降雨强度为60mm/h;峰值型:降雨强度分布为30-90-60mm/h;延迟型:降雨强度分布为60-30-90mm/h;减弱型:降雨强度分布为90-60-30mm/h),研究降雨雨型变化对东北黑土区坡耕地土壤侵蚀的影响。结果表明:各雨型条件下休闲坡耕地径流总量的大小顺序为延迟型>减弱性>均匀型>峰值型,而土壤侵蚀总量的大小顺序为减弱型>均匀型>延迟型>峰值型。延迟型雨型的坡面径流总量是其它雨型的1.02~1.45倍,减弱型降雨的侵蚀总量分别是均匀型、延迟型和峰值型的1.03、1.36和2.68倍。同一雨强在不同降雨雨型中出现的位置不同,其产生的坡面径流量和侵蚀量对坡面总径流量、总侵蚀量的贡献率也不同,分布在降雨雨型起始位置的雨强对坡面径流量的贡献率最小;除30mm/h降雨强度外,分布在降雨雨型起始位置的雨强对坡面侵蚀的贡献率最大。研究还发现,试验设计中减弱型降雨雨型与东北黑土区夏季主要侵蚀雨型特点类似,是造成东北黑土区坡耕地土壤侵蚀相对严重的主要雨型。