化学模式识别法在钢铁工业中的若干应用

本文涉及一种崭新的非函数数据处理法及其在工业诊断和优化中的应用。并对其进行要因分析和优化决策的原理作了介绍。结合钢铁工业生产中的实例进行了分析。还探讨了该方法在钢铁工业中应用的意义。     

An expert PID controller uses refined ziegler and nichols rules and fuzzy logic ideas

This article proposes a scheme for the on-line adjustment of three mode controller settings based on experimental measurements of closed-loop performance. It uses a recently developed heuristic tuning procedure to identify estimated process parameters. This method may give rise to conflicting estimates. Fuzzy Set theory is applied to manage the situation in terms of a fuzzy conjunction to combine the various estimates. PID control was chosen because of its wide use in the industrial environment due to driving simplicity and robustness. The article shows design, development, and computer simulation aspects.     

无端点检测汉语识别算法的实现及改进——动态时间规整和隐马尔可夫统一模型的应用

语音识别算法中，动态时间规整（ＤＴＷ）和隐马尔可夫模型（ＨＭＭ）是最有效的识别算法，并且两者之间有着本质的联系和内在的统一［１］，据此前期工作中，已经建立了ＤＴＷ和ＨＭＭ的统一模型（ＤＨＵＭ）［２、３］。本文对ＤＨＵＭ进行了改进，在ＤＨＵＭ中引进寂静段自环，并根据汉语语音的特点，提出了一种无端点检测的语音识别算法。在识别过程中，该算法无需确定语音信号起止点位置，而是从寂静段开始，直接按帧提取特征（帧长２０ｍｓ，帧间重叠５０％），特征向量由１５阶倒谱系数和帧平均能量组成。实验中，用ＤＨＵＭ实现了该算法，对９９个相似汉语单字的识别测试结果表明：无端点检测的识别正识率为９４．９５％，正识率下降很少，但不作端点检测却降低了算法的复杂程度。为进一步改善识别性能，特征向量采用一种听觉模型特征，识别器具有更好的鲁棒性，识别率会略有提高。     

手写体汉字识别问题综论

本文在讨论了人对汉字的认知心理试验研究结果之后,认为人类的汉字识别是经由整字属性及分层结构的多种途径复合而成的。这些途径中的大多数都可以在手写体汉字的机器识别中模仿运用。由此可把汉字的机器识别方法归纳为整模式法和子模式法两个大类,对它们的有利方面和困难方面进行了讨论;对影响其性能的因素进行了分析;对识别率以及它与识别字集大小和后处理等的关系提出了评估的问题。     

通用PRIP程序设计语言EPPPI的设计

本文介绍了一种同时具有PASCAI和PROLOG语言特点的通用的模式识别和图象处理(PRIP)程序设计语言EPPPL,相对于PASCAL,EPPPI包含了抽象级更高的数据类型和相应的公共操作.因而该语言具有比PASCAL更强的描述能力,使在科学计算程序设计时有更高的效率.文中论证了在EPPPI中引入PROLOG机制的可行性.由于在EPPPI中包含了PROLOG的机制,使该语言适用于人工智能程序设计,并具有陈述式特点,因而使它的编程效率更进一步提高.     

Self-calibration based on invariant view recognition: Dynamic approach to navigation

We extend a dynamic approach of behavior generation to the representation of spatial information. Two levels of dynamics integrate dead-reckoning, dominant far from home bases, and piloting, dominant near home bases. When the view-based piloting system recognizes a home base, visual place information recalibrates the dead-reckoning system, inverting the hierarchical ordering of the two dynamic levels by time scale inversion. Reference views taken at discrete home bases are recognized invariantly under rotation of views. This process yields compass information. Continuous translational information is obtained as a neural place representation built from view correlations with a scattered set of local views. This self-calibrating cognitive map couples into a dynamics of heading direction integrating the behaviors of obstacle avoidance and target acquisition. Targets can be designated in terms of the cognitive map. We demonstrate the dynamical model in simulation.     

Optical pattern recognition using two-channel joint transform correlation

A new joint transform correlation (JTC) technique, named two-channel JTC (TJTC), is proposed in this paper for optical pattern recognition applications. The TJTC technique independently evaluates the autocorrelation and crosscorrelation values of the reference and the target images and employs a modified decision algorithm. In addition, optical threshold operation and fringe-adjusted filter are incorporated in the proposed technique to enhance the correlation output and to improve the discrimination performance. The proposed technique shows better recognition performance compared to existing JTC techniques. Computer simulation are presented to investigate the salient features of the proposed TJTC technique with noise-free as well as noisy input scenes. The text was submitted by the authors in English.     

Laplace spectra as fingerprints for image recognition

In the area of image retrieval from data bases and for copyright protection of large image collections there is a growing demand for unique but easily computable fingerprints for images. These fingerprints can be used to quickly identify every image within a larger set of possibly similar images. This paper introduces a novel method to automatically obtain such fingerprints from an image. It is based on a reinterpretation of an image as a Riemannian manifold. This representation is feasible for gray value images and color images. We discuss the use of the spectrum of eigenvalues of different variants of the Laplace operator as a fingerprint and show the usability of this approach in several use cases. Contrary to existing works in this area we do not only use the discrete Laplacian, but also with a particular emphasis the underlying continuous operator. This allows better results in comparing the resulting spectra and deeper insights in the problems arising. We show how the well known discrete Laplacian is related to the continuous Laplace-Beltrami operator. Furthermore, we introduce the new concept of solid height functions to overcome some potential limitations of the method.     

一个基于神经网络的专家系统

医疗专家系统主要使用基于知识的技术，其中的决策规则和策略来自于人类的专家。把这些知识和各种推理方法结合，可以建立一个模拟专家决策过程的系统。建立这样一个系统，需要经常与专家磋商，以获取专家的知识，因而需要大量的时间和精力。为此，本文提出直接从数据中提取有效的信息，即用神经网络提取隐含在大量数据中对医疗诊断有效的信息，继之与基于规则的知识，各种推理方法相结合，建立一个神经网络专家系统。     

Target differentiation with simple infrared sensors using statistical pattern recognition techniques

This study compares the performances of various statistical pattern recognition techniques for the differentiation of commonly encountered features in indoor environments, possibly with different surface properties, using simple infrared (IR) sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the differentiation process. We construct feature vectors based on the parameters of angular IR intensity scans from different targets to determine their geometry and/or surface type. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. Parametric differentiation correctly identifies six different surface types of the same planar geometry, resulting in the best surface differentiation rate (100%). However, this rate is not maintained with the inclusion of more surfaces. The results indicate that the geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. The results demonstrate that simple IR sensors, when coupled with appropriate processing and recognition techniques, can be used to extract substantially more information than such devices are commonly employed for.