L2(Rd)(d≥3)空间非张量积样条小波基的构造

本文提出了 L2 (Rd)空间小波基的一种新型构造方法 ,此方法构造出来的小波基不能由张量积产生。     

基于均匀设计的精密排种器结构优化方法

采用均匀设计方法进行了气吹式精密排种器常压下播种大豆试验,考察了排种器结构参数(充种角、清种角)与性能参数之间的关系,建立了粒距合格率、种子充填率与排种器结构参数之间的数学模型,获得了回归方程和最优结构参数。常压下播种大豆时,充种角和清种角最优化值分别为46.35°和55.05°,对气吹排种器设计具有指导意义。     

Uniform Approximation of Discrete-Time Periodically Varying Systems

It is shown that the elements of a large class of discrete-time periodically varying nonlinear input-output maps can be uniformly approximated arbitrarily well, over infinite time intervals, using a certain structure that can be implemented in many ways using, for example, radial basis functions, polynomial functions, piecewise linear functions, sigmoids, or combinations of these functions. For the special case in which these functions are taken to be certain polynomial functions, the input-output map of our structure is a generalized finite discrete-time Volterra series. Results are given for the case in which inputs and outputs are defined on the integers. The case in which inputs and outputs are defined on the nonnegative integers is also addressed.     

Speech recognition using pulse-coupled neural networks with a radial basis function

We have developed a novel pulse-coupled neural network (PCNN) for speech recognition. One of the advantages of the PCNN is in its biologically based neural dynamic structure using feedback connections. To recall the memorized pattern, a radial basis function (RBF) is incorporated into the proposed PCNN. Simulation results show that the PCNN with a RBF can be useful for phoneme recognition. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

Adaptive Beamforming and DOA Estimation Using Uniform Concentric Spherical Arrays with Frequency Invariant Characteristics

This paper proposes a new digital beamformer for uniform concentric spherical array (UCSA) having nearly frequency invariant (FI) characteristics. The basic principle is to transform the received signals to the phase mode and remove the frequency dependency of the individual phase mode through the use of a digital beamforming network. It is shown that the far field pattern of the array is determined by a set of weights and it is approximately invariant over a wide range of frequencies. FI UCSAs are electronic steerable in both the azimuth and elevation angles, unlike their concentric circular array counterpart. The frequency invariant characteristic of the FI UCSA also makes it possible to design separately the compensation network and beamformer weighting coefficients. The design of the compensation network is formulated as a second order cone programming (SOCP) problem and is solved optimally for minimax criterion. Thanks to the frequency invariant characteristic, traditional narrow band adaptive beamforming algorithms such as minimum variance beamforming (MVB) can be applied to the FI UCSA. Also, traditional narrow band 2-D direction of arrival (DOA) estimation algorithms such as unitary ESPRIT can be extended to broadband DOA estimation using FI UCSA. Simulation results show that the proposed adaptive beamformer using FI UCSA can obtain a higher output signal to inference plus noise ratio over the conventional tapped-delay line approach. Simulation results also show that FI UCSA has uniform beampattern and resolution around 360° in both azimuth and elevation angles, unlike FI uniform concentric circular array. The usefulness of the proposed UCSA-FIB in broadband 2-D DOA estimation is also verified by computer simulation.

结合灰色理论的人工神经网络方法 在水质预测中的应用

针对现阶段水质监测中存在的水质变化响应滞后问题,提出了采用灰色预测法、人工神经网络(BP神经网络、径向基神经网络、广义回归神经网络)以及两者组合的方法对水质动态预测进行研究。以太湖流域嘉兴斜路港监测断面为例,并依据后验差检验比值c及小概率精度p对模型预测效果进行了分析。结果表明,对年内预测,通过广义回归神经网络的动态预测值平均相对误差为0.61%,后验差检验比值小于0.65,小误差概率大于0.7;采用灰色结合广义回归神经网络的方法对水质pH值进行预测,平均相对误差仅有0.85%,后验差检验比值小于0.65,小误差概率等于1。研究结果还表明,对年际预测,灰色结合BP神经网络和灰色结合径向基函数神经网络的动态预测值平均相对误差分别为0.57%和0.80%,其后验差比值都小于0.5,小概率误差都为0.9,大于0.8。     

基于小波技术的曲面边界光顺及简化算法

与传统造型方法相比,T 样条曲面具有曲面拼接、局部加细、数据简化等特点。基于 T 样条曲 面的非矩形拓扑结构及 B 样条小波的滤波优势,提出了一种曲面边界光顺及简化算法。与传统方法相比,该算 法基于非均匀 B 样条小波分解,对选定的曲面边界进行光顺,并利用 T 样条技术减少冗余控制点。最后,给 出具体实例以验证算法的有效性和实用性。     

均匀设计方法在水电站发电调度优化中的应用研究

水电站工程的科学调度是实现水资源优化配置、发挥工程效益的重要方式和有效手段。文章以水丰水电站为例,进行了均匀设计方法在水电站发电优化调度中的应用研究,结果显示该方法与传统优化方法相比具有明显优势,可以用于水电站发电调度优化研究。     

A Fast Algorithm to Map Functions Forward

Mapping functions forward is required in image warping and other signal processing applications. The problem is described as follows: specify an integer d 1, a compact domain D R ^d, lattices L ₁,L ₂ R ^d, and a deformation function F : D R ^d that is continuously differentiable and maps D one-to-one onto F(D). Corresponding to a function J : F(D) R, define the function I = J F. The forward mapping problem consists of estimating values of J on L ₂ F(D), from the values of I and F on L ₁ D. Forward mapping is difficult, because it involves approximation from scattered data (values of I F ^-1 on the set F(L ₁ $#x22C2; D)), whereas backward mapping (computing I from J) is much easier because it involves approximation from regular data (values ofJ on L ₂ D). We develop a fast algorithm that approximates J by an orthonormal expansion, using scaling functions related to Daubechies wavelet bases. Two techniques for approximating the expansion coefficients are described and numerical results for a one dimensional problem are used to illustrate the second technique. In contrast to conventional scattered data interpolation algorithms, the complexity of our algorithm is linear in the number of samples.