Truncated Newton method for sparse unconstrained optimization using automatic differentiation

When solving large complex optimization problems, the user is faced with three major problems. These are (i) the cost in human time in obtaining accurate expressions for the derivatives involved; (ii) the need to store second derivative information; and (iii), of lessening importance, the time taken to solve the problem on the computer. For many problems, a significant part of the latter can be attributed to solving Newton-like equations. In the algorithm described, the equations are solved using a conjugate direction method that only needs the Hessian at the current point when it is multiplied by a trial vector. In this paper, we present a method that finds this product using automatic differentiation while only requiring vector storage. The method takes advantage of any sparsity in the Hessian matrix and computes exact derivatives. It avoids the complexity of symbolic differentiation, the inaccuracy of numerical differentiation, the labor of finding analytic derivatives, and the need for matrix store. When far from a minimum, an accurate solution to the Newton equations is not justified, so an approximate solution is obtained by using a version of Dembo and Steihaug's truncated Newton algorithm (Ref. 1).This paper was presented at the SIAM National Meeting, Boston, Massachusetts, 1986.     

应用自动微分的Newton-PCG算法

一类新的使用符号微分的Newton-PCG型算法在文献[1]和[2]被导出来了。本文建立和研究应用自动微分的相应的Newton-PCG算法，理论分析和数值实验结果显示应用自动微分之后，目标函数的维数或复杂性越大，Newton-PCG算法对Newton法的改进越显著。     

Robust Speed Control of a Low Damped Electromechanical System Based on CRONE Control: Application to a Four Mass Experimental Test Bench

Robust speed control of a low damped electromechanical system with backlash is studied, controlled load angular speed being not measured. The proposed control strategy combines a Luenberger observer (load angular speed and load torque disturbance estimations) and a robust CRONE controller. The observer provides estimation of the load angular speed and of the disturbance torque applied on the load. Through the computation of only three independent parameters (as many as a PID controller), the CRONE controller permits to ensure the robust speed control of the load in spite of plant parametric variations and speed observation errors. The proposed control strategy is applied to a four mass experimental test bench.     

Impact of Partial Separability on Large-Scale Optimization

ELSO is an environment for the solution oflarge-scale optimization problems. With ELSO the user is required to provide only code for the evaluation of a partially separable function. ELSO exploits the partialseparability structure of the function to computethe gradient efficiently using automatic differentiation.We demonstrate ELSO's efficiency by comparing thevarious options available in ELSO.Our conclusion is that the hybrid option in ELSOprovides performance comparable to the hand-coded option, while having the significantadvantage of not requiring a hand-coded gradient orthe sparsity pattern of the partially separable function.In our test problems, which have carefully coded gradients,the computing time for the hybrid AD option is within a factor of two of thehand-coded option.     

A Supergene Differentiation Model for Orebearing Granitic Magma

According to the features of geophysics, experimental petrology, granite geology and geochemistry, the differentiations of ore-bearing granitic magmas are discussed. It is put forward that only the supergene differentiations of ore-bearing granitic magma might exist, instead of the hypogene one of the magma. Based on it, a supergene differentiation model for the ore-bearlng granitic magma is presented.     

Numerical differentiation from a viewpoint of regularization theory

In this paper, we discuss the classical ill-posed problem of numerical differentiation, assuming that the smoothness of the function to be differentiated is unknown. Using recent results on adaptive regularization of general ill-posed problems, we propose new rules for the choice of the stepsize in the finite-difference methods, and for the regularization parameter choice in numerical differentiation regularized by the iterated Tikhonov method. These methods are shown to be effective for the differentiation of noisy functions, and the order-optimal convergence results for them are proved.

     

KNbO3：Fe晶体的时间微分效应及图像追踪

本文观察到了KNbO_3:Fe晶体的时间微分效应,并用这个微分效应进行了图像追踪的演示,为KNbO_3:Fe晶体在光折变器件领域的应用进行了有益的探索。     

Isomer effects on transport properties of polyesters based on bisphenol-A

Pure gas sorption and transport properties of polyesters based on bisphenol-A and both pure isophthalic and pure terephthalic acid chloride were obtained for He, N₂, O₂, CH₄, and CO₂ at 35°C. The polymers were synthesized in our laboratory and amorphous films were prepared with a specialized solvent casting procedure. The polymer containing m-phenylene groups shows higher permselectivity for most of the gas pairs. The ideal selectivity of O₂/N₂ was increased by 33% when p-phenylene units were replaced by m-phenylene ones. On the other hand, the polyester containing only p-phenylene groups, shows higher permeability to all the gases studied. The polymer based on pure terephthalic acid chloride has a 75% higher oxygen permeability and a 1.1-fold higher carbon dioxide permeability than the isophthalic acid derivative. The polyester containing meta-phenylene units has lower T_g, higher permselectivity, lower permeability, lower fractional free volume (FFV), and lower d-spacing. The values of FFV, and lower d-spacing. The values of FFV and d-spacing were only slightly different between the two isomers. Moreover, for the sub-T_gγ transition the maximum in tan δ occured at essentially the same temperature (?55°C). The polymer with a higher concentration of p-phenylene units shows somewhat larger area under the γ-peak, indicating slightly more sub-T_g motion. The Distribution of FFV is considered to be the determining factor for the differences in transport properties observed. © 1993 John Wiley & Sons, Inc.