基于广义BP算法的模型参考自适应控制

改进了传统的神经网络BP算法,提出了基于广义BP算法的非线性不确定系统的神经网络模型参考自适应控制方案.并将其用于非线性不确定系统的控制,仿真实验表明了控制器具有良好的非线性控制性能.     

集值映射Henig有效解的最优性条件

在锥偏序Banach空间中利用集值映射的上图导数引进了Henig有效意义下的广义梯度,在一定条件下,利用凸集分离定理证明了该广义梯度的存在性。作为应用,给出了用广义梯度刻画集值优化问题Henig有效解的充分条件。     

广义对称矩阵的特征根

本文得到了一个新的广义对称矩阵的充分必要条件,并且给出了广义对称矩阵的每个特征根的估计.     

广义Lagrange中值定理的逆定理

本文证明了若f(x)是[a,6]上的凸函数,则广义Lagrange中值定理逆定理成立。     

关于由广义的Fibonacci数构成的倒数和及其交错和的若干性质

本文给出了由广义的Fibonacci数构成的倒数和及其交错和之间的某种联系.     

On generalized extending modules

A module M is called generalized extending if for any submodule N of M, there is a direct summand K of M such that N≤K and K/N is singular. Any extending module and any singular module are generalized extending. Any homomorphic image of a generalized extending module is generalized extending. Any direct sum of a singular (uniform) module and a semi-simple module is generalized extending. A ring R is a right Co-H-ring if and only if all right R modules are generalized extending modules.     

广义Lupas-Baskakov积分算子的同时逼近

讨论了广义Lupas-Baskakov积分算子的同时逼近，推广了[3]中一些结果，得到了逼近阶的估计。     

关于广义Riccati方程的可积条件——与赵临龙先生商榷

指出《科学通报》1998年第1《Riccati微分方程一个新的可积条件》中的错误并给出正确结论，即方程y’=P（x）y^n＋Q（x）y＋R（x）的可积条件不是R=K’Pe^n∫ （Q-βD）dx（K＇β为常数），而是[Q-1-n（R＇/R-P＇/P）]^n／PR^n-1=r（r为常数）．给出了满足这一条件的方程的通积分；推广了该方程原有的可积条件R=KPe^n∫Qdx（K为常数）．     

A Simulation Study Evaluating the Generalized Additive Model for Assessing Intervention Effects with Small Samples

Single subject (SS) designs are popular in educational and psychological research. There exist several statistical techniques designed to analyze such data and to address the question of whether an intervention has the desired impact. Recently, researchers have suggested that generalized additive models (GAMs) might be useful for modeling nonlinear effects that are common with SS designs. This study sought to extend the use of GAM from SS to a research design in which individuals may be placed in separate groups and receive different interventions. Results of the simulation study found that using a mixed model form of GAM (GAMM) resulted in higher power for detecting actual effects in the population than was true for either GAM or a Bayesian GAM estimator. Thus, GAMMs are recommended for use with SS designs when interventions are expected to induce nonlinear relationships between time and the outcome variable and individuals receive different treatments.     

Shift-invariance of short-time Fourier transform in fractional Fourier domains

Fractional Fourier domains form a continuum of domains making arbitrary angles with the time or frequency domains on the time-frequency plane. Signal representations in these domains are related to the fractional Fourier transform (FrFT). In this paper, a new proof on the shift-invariance of linear time-frequency distributions on fractional Fourier domains is given. We show that short-time Fourier transform (STFT) is the unique linear distribution satisfying magnitude-wise shift-invariance in the fractional Fourier domains. The magnitude-wise shift-invariance property in arbitrary fractional Fourier domains distinguishes STFT among all linear time-frequency distributions and simplifies the interpretation of the resultant distribution as shown by numerical examples.