基于约束优化的联想记忆模型学习算法

本文提出了一种对称互连神经元网络的学习策略,利用全局约束优化方法确定连接权。优化过程采用了梯度下降技术。这种学习算法可以保证训练样本成为系统的稳定吸引子,并且具有优化意义上的最大吸引域。本文讨论了网络的存储容量,训练样本的渐近稳定性和吸引域大小。计算机实验结果说明了学习算法的优越性。     

TEMIC射频卡的速率自适应读卡算法

提出种基于TEMIC射频卡Manchester编码的速率自适应读卡算法,并对该算法进行了说明和示例。     

Local polynomial fitting under association

We consider the estimation of multivariate regression functions r(x₁,…,x_d) and their partial derivatives up to a total order p1 using high-order local polynomial fitting. The processes {Y_i,X_i} are assumed to be (jointly) associated. Joint asymptotic normality is established for the estimates of the regression function r and all its partial derivatives up to the total order p. Expressions for the bias and variance/covariance matrix (of the asymptotic distribution) are given.     

A parallel version of the preconditioned conjugate gradient method for boundary element equations

The parallel version of precondition techniques is developed for matrices arising from the Galerkin boundary element method for two-dimensional domains with Dirichlet boundary conditions. Results were obtained for implementations on a transputer network as well as on an nCUBE-2 parallel computer showing that iterative solution methods are very well suited for a MIMD computer. A comparison of numerical results for iterative and direct solution methods is presented and underlines the superiority of iterative methods for large systems.     

A geometric theory forL 2-stability of the inverse problem in a one-dimensional elliptic equation from anH 1-observation

This study provides a stability theory for the nonlinear least-squares formulation of estimating the diffusion coefficient in a two-point boundary-value problem from an error-corrupted observation of the state variable. It is based on analysing the projection of the observation on the nonconvex attainable set.This research was started while G. Chavent visited the Technical University of Graz. Support through the Steiermaerkische Landesregierung is gratefully acknowledged.     

BAHADUR ASYMPTOTIC EFFICIENCY IN A SEMIPARAMETRIC REGRESSION MODEL

ＢＡＨＡＤＵＲＡＳＹＭＰＴＯＴＩＣＥＦＦＩＣＩＥＮＣＹＩＮＡＳＥＭＩＰＡＲＡＭＥＴＲＩＣＲＥＧＲＥＳＳＩＯＮＭＯＤＥＬ￥ＬＩＡＮＧＨＵＡ；ＣＨＥＮＧＰＩＮＧＡｂｓｔｒａｃｔ：ＴｈｅａｕｔｈｏｒＳｇｉｖｅＭＬＥθ１ＭＬｏｆθ１ｉｎｔｈｅｍｏｄｅｌＹ＝θ...     

Analysis and implementation of cross sync period underwater acoustical positioning techniques for underwater targets

I.IlltroductionWhenanactiveunderwateracousticalpositioningsystemissearchingforanunderwatertarget,itisnecessaryforittocompleteatransmittingandreceivingcycIewithineachworkingperiodinordertofindoutthelocationofthetargetcorrectly.Forexample,whenanunder-wateracoustica1synchronouspositioningsystemistrackinganunderwatertargetwithagivensynchr0nizingperiod,thepropagati0ntimeofthepositioningsignaltravellingfr0mthetaJrgettothearrayofthesystemshouldbelessthanthesynchronizingperiod0therwisetargetdis-tance…     

一种放射CT重建的鲁棒估计算法

放射CT的重建问题可以归结为一种基于泊松分布的最大似然估计（MuxnimumLikelihood,ML），其中最著名的如EM算法[1]，这种算法存在的问题是鲁棒性不强，当观测数据中存在一些出格点（outlier）（如2％）时，EM算法的性能就变得很差。本文分析了算法性能变差的原因，将泊松分布近似为高斯分布后，仿照鲁律估计中的M-估计，构造了一种鲁棒性很强的EM改进算法。实验结果表明，即使在投影数据中混有10％的出格点，仍能重建出满意的结果来。     

CROSS-SPECTRAL MOMENT AND SVD METHODS ESTIMATING THE PARAMETERS OF CLOSE SINUSOIDS IN COLORED NOISE

The cross-spectral estimation methods are efficient in estimating the parameters of sinusoidal signals embedded in colored noise. But up to now, only FPT and cross-periodogram methods are used in this field, the modern auto-spectral estimation method is introduced into cross-spectral estimation in this paper, meanwhile the cross-correlation based Yule-Walker equation is proposed theoretically and the moment and singular-value decomposition (SVD)) algorithms for cross-spectral estimation have been developed. Finally, a numerical example is given for comparing the presented methods with the well-known Cadzow's SVD method.     

自适应有源噪声控制的滤波-LMAD算法

本文研究了稳定非高斯环境下的自适应有源噪声控制问题，提出了滤波－ＬＭＡＤ（ｌｅａｓｔｍｅａｎａｂｓｏｌｕｔｅｄｅｖｉａｔｉｏｎ）算法及归一化滤波－ＬＭＡＤ算法，仿真结果表明，与常用的滤波－ＬＭＳ算法和归－化滤波－ＬＭＳ算法相比，本文提出了算法收敛速度更快。