Boole函数的线性可分性(Ⅰ)——n-维超立方体的基本理论

Boole函数的线性可分性是前向人工神经网络理论中的一个比较困难的问题之一。目前仅对变量数n≤7的某些问题给予讨论。当n≥8时,尚无判别Boole函数线性可分的一般准则,更无线性可分Boole函数的计数公式。基于此,本文详细地研究了与Boole函数线性可分性有关的n-维超立方体的基本理论,包括n-维超立方体的基本性质、超立方体中的平行线、子超立方体的计数等,并给出了构造n-维超立方体图的一种新方法。     

提高前馈神经网络推广能力的若干实际方法

提高前馈神经网络的推广能力是深受关注的问题，本文根据我们最近提出了一个网络有效推广的准则，从提高网络特征提取能力，分类能力和修改神经元激活函数等几方面给出了若干实际方案，我们在任意手写数字识别问题上的实验结果证实了这些方法的有效性。     

QSAR Modeling of Large Heterogeneous Sets of Molecules

Abstract

In aquatic toxicology, QSAR models are generally designed for chemicals presenting the same mode of toxic action. Their proper use provides good simulation results. Problems arise when the mechanism of toxicity of a chemical is not clearly identified. Indeed, in that case, the inappropriate application of a specific QSAR model can lead to a dramatic error in the toxicity estimation. With the advent of powerful computers and easy access to them, and the introduction of soft modeling and artificial intelligence in SAR and QSAR, radically different models, designed from large non-congeneric sets of chemicals have been proposed. Some of these new QSAR models are reviewed and their originality, advantages, and limitations are stressed.     

ENTROPY IMMUNITY OF FEEDFORWARD NETWORKS

Siegenthaler's“Correlation Immunity”concept has been improved in this paper.From practical points of view,the new concept is more powerful than the original one in avoid-ing the trade-off between“the order of correlation immunity”and“the linear complexity”of keystreams in cipher system.Bent functions are also introduced into the studies of linear approxima-tion and entropy immunity for feedforward networks.New results and new methods are presentedalso.     

Test Problem Generator by Neural Network for Algorithms that Try Solving Nonlinear Programming Problems Globally

A test problem generator, by means of neural networks nonlinear function approximation capability, is given in this paper which provides test problems, with many predetermined local minima and a global minimum, to evaluate nonlinear programming algorithms that are designed to solve the problem globally.     

Linear feedforward control of two-level quantum system by modulated external field

We propose a model of feedforward (open-loop) optical control of two-level atom in the linear form. This model allows to express the general form of solution for the atomic level populations via the arbitrary shapes of the control signal. Then we make numerical investigations of different shapes for the optical control signal.     

Evaluation of fuzzy regression models by fuzzy neural network

In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy linear and nonlinear regression models with fuzzy output and crisp inputs, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples.     

Data-based spatial feedforward for over-actuated motion systems

For advanced motion systems there is an increasing demand for higher production throughput and accuracy. Traditionally, such systems are designed using a rigid-body design paradigm, which aims at designs with high stiffness. The alternative is to design a lightweight system and deal with the resulting flexibilities by over-actuation and over-sensing. This paper presents a data-based spatial feedforward method based on previous task trials, which aims at reducing the vibrations over the complete structure during motion. The proposed method is experimentally validated on an industrial prototype and compared to standard mass feedforward using rigid-body decoupling.     

A process-tolerant out-of-band blocker rejection technique for SAW-less receivers

In this paper, an active filtering technique is presented which is capable of filtering the out-of-band blockers in wireless receivers. The concept is based on the feedforward cancellation technique where a blocker replica is subtracted at the output of the low-noise amplifier (LNA). In contrast to the previously reported feedforward cancellation methods, exact gain and phase matching are easily obtained in the proposed architecture to produce a highly selective narrowband frequency response at the output of the LNA with wide rejection bandwidth. For the proof of concept, the system is implemented in a 65 nm CMOS technology. It occupies a total area of 0.8 mm² and the current consumption is 24 mA from a 1.2 V supply. The system post-layout simulations showed a blocker rejection of more than 33 dB for blocker signals 100 MHz away from the desired signal when the feedforward path is activated. The noise figure (NF) of the entire system is 3.8 dB that degrades to 5.8 dB when the feedforward path is activated.