联想

“妈妈，你看我的连笔字写得漂亮吗？” “看到你写的字，我就联想起没有月光的黑夜。” “我的字真的富有诗意吗？”

关于《联想风云》

“你来了解一下我们的企业吧!”柳传志盯着我说．“你一定会感兴趣的。”

风云飘四海——《联想风云》英文版全球上市经验谈

版权贸易是出版领域中重要的一块领地。无论是从国外引进图书版权,还是向国外输出图书版权,都是扩大图书出版领地、赢得市场份额的重要手段之一。随着我国图书市场化、国际化程度的不断提高,引进版权的图书出版和图书版权的海外销售,已经成为很多出版社日常工作中不可或缺的组成部分。这里介绍的十本优秀图书的版权故事,是我们特约出版社一线版权人士或编辑亲笔撰写的文章。尽管每本图书的版权交易各不相同,但从中我们仍然可以得到很多有益的启示。

联想的第287名员工

“我不写了，再写下去就把自己写死了!”1988年的某天，当时已是北京市作家协会会员的陈惠湘，在自己的“文学导师”韩少华面前大吐着“苦水”。

联想室里学联想

且说三客霞拿着“比喻室”发给他们的纪念章，十分高兴。

Implicative and Fuzzy Implicative Ideals of Lattice Implication Algebras

In this paper, we defined the concept of implicative and fuzzy implicative ideals of lattice implication algebras, and discussed the properties of them. And then, we pointed out the relations between implicative ideal and LI _ideal, implicative iedal and implicative filter, implicative ideal and fuzzy implicative ideal, fuzzy implicative ideal and fuzzy implicative filter, and fuzzy implicative ideal and fuzzy LI _ideal.

The Processing Mechanism of Associative Meaning Under the Cognitive Context Based on Culture

Cognitive context is the cognitionalized context of language, situation and context of culture by the individual which is stored and stimulated in individual＇s mind when meaning is processed. The focus of this article is on context of culture cognitionalized by individuals. Cognitive context based on culture is the inner force of the processing of associative meaning. Cognitive context reflects the similarities and differences of the understanding of different cultural communities towards the world around them.

A Novel Multivalued Associative Memory System

Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.

Traffic light detection and recognition in intersections based on intelligent vehicle

To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.

DISCRETE BIDIRECTIONAL ASSOCIATIVE MEMORY WITH LEARNING FUNCTION

In this paper we propose a new discrete bidirectional associative memory (DBAM) which is derived from our previous continuous linear bidirectional associative memory (LBAM). The DBAM performs bidirectionally the optimal associative mapping proposed by Kohonen. Like LBAM and NBAM proposed by one of the present authors,the present BAM ensures the guaranteed recall of all stored patterns,and possesses far higher capacity compared with other existing BAMs,and like NBAM, has the strong ability to suppress the noise occurring in the output patterns and therefore reduce largely the spurious patterns. The derivation of DBAM is given and the stability of DBAM is proved. We also derive a learning algorithm for DBAM,which has iterative form and make the network learn new patterns easily. Compared with NBAM the present BAM can be easily implemented by software.

BIDIRECTIONAL ASSOCIATIVE MEMORY ENSEMBLE

The multiple classifier system （MCS）, composed of multiple diverse classifiers or feed-forward neural networks, can significantly improve the classification or generalization ability of a single classifier. Enlightened by the fundamental idea of MCS, the ensemble is introduced into the quick learning for bidirectional associative memory （QLBAM） to construct a BAM ensemble, for improving the storage capacity and the error-correction capability without destroying the simple structure of the component BAM. Simulations show that, with an appropriate ＂overproduce and choose＂ strategy or ＂thinning＂ algorithm, the proposed BAM ensemble significantly outperforms the single QLBAM in both storage capacity and noise-tolerance capability.

STABILITY OF THE HIGH-ORDER BAM AND ITS PERFORMANCE ANALYSIS

High order bidirectional associative memory (HOBAM) by Tai et al is extension to Kosko′s bidirectional associative memory(BAM). It not only possesses merits of the BAM, but also relaxes the continuity assumption for reliable recalls and significantly improves the storage capacity and error correcting capability of the BAM. However, Tai′s performance analysis for the HOBAM is only limited in the computer simulations, in the other words, they did not give a theoretical analysis result. This paper fills the blank and gives a theoretical proof for HOBAM′s stability and storage capacity analysis so that the system can theoretically ensure all the training pattern pairs to become its stable points.

Reconstruction based approach to sensor fault diagnosis using auto-associative neural networks

Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal component analysis(NLPCA)should be applied.In this work,NLPCA based on auto-associative neural network(AANN)was applied to model a chemical process using historical data.First,the residuals generated by the AANN were used for fault detection and then a reconstruction based approach called enhanced AANN(E-AANN)was presented to isolate and reconstruct the faulty sensor simultaneously.The proposed method was implemented on a continuous stirred tank heater(CSTH)and used to detect and isolate two types of faults(drift and offset)for a sensor.The results show that the proposed method can detect,isolate and reconstruct the occurred fault properly.

柳传志驻足台湾岛的反思

1998年的这个春天．联想发生了一些变化．无形却又意义重大过去在市场上追着人家跑．现在被人家追着跑．这是其一．过去需要钱的地方太多．却没有钱．现在兜里装了那么多现金．却不知道该怎么花．这是其二：过去公司很小．却总是口气很大．觉得自己能行走天下．现在公司大了．却又常常觉得寸步难行。20世纪80年代末期进入公司的一代新人如今全都成熟了．杨元庆在市场上的成功．

Proximity association in polygynous western black crested gibbons (Nomascus concolor jingdongensis): network structure and seasonality

We investigated the structure and seasonality of the proximity network in a group of polygynous western black crested gibbons (Nomascus concolor) using social network analysis. The spatial proximity changed seasonally and was affected by temperature and rainfall. Preferred proximity association was not distributed randomly among individuals. Kinship was one explanation for the social structure, as offspring preferred to maintain close proximity with their mothers. The proximity of infants to mothers decreased with age, and independent offspring had lower proximity to mothers than dependent ones. We found that the adult male had different proximity relationships with two different adult females. The frequency of proximity between the male and the infant-carrying female was significantly higher than that between the male and the female who had immigrated carrying one offspring of uncertain paternity into the group. Infanticide avoidance and/or predation protection for dependent infants might explain the proximity relationship differences. Temperature influenced group proximity association, with individual proximity increasing in the cold months and decreasing in the hot months. Group proximity decreased in months with higher anthropogenic disturbance.

Soft sensor of chemical processes with large numbers of input parameters using auto-associative hierarchical neural network

To explore the problems of monitoring chemical processes with large numbers of input parameters, a method based on Auto-associative Hierarchical Neural Network(AHNN) is proposed. AHNN focuses on dealing with datasets in high-dimension. AHNNs consist of two parts: groups of subnets based on well trained Autoassociative Neural Networks(AANNs) and a main net. The subnets play an important role on the performance of AHNN. A simple but effective method of designing the subnets is developed in this paper. In this method,the subnets are designed according to the classification of the data attributes. For getting the classification, an effective method called Extension Data Attributes Classification(EDAC) is adopted. Soft sensor using AHNN based on EDAC(EDAC-AHNN) is introduced. As a case study, the production data of Purified Terephthalic Acid(PTA) solvent system are selected to examine the proposed model. The results of the EDAC-AHNN model are compared with the experimental data extracted from the literature, which shows the efficiency of the proposed model.

Combining TOPSIS and GRA for supplier selection problem with interval numbers

Supplier selection can be regarded as a typical multiple attribute decision-making problem. In real-world situation, the values of the alternative attributes and their weights are always being nondeterministic, and as a result of this, the values are considered interval numbers. In addition, the common approach to measure the similarity between alternatives through their distance suffers from some minor shortcomings. To address these problems, this study develops a novel hybrid decision-making method by combining the technique for order preference by similarity to an ideal solution （TOPSIS） with grey relational analysis （GRA） for supplier selection with interval numbers. By introducing the intervals theory, the extensions of Euclidean distance and grey relational grade are defined. And then a new comprehensive closeness coefficient is constituted for supplier alternatives evaluation based on the interval Euclidean distance and the interval grey relational grade, which could indicate the distance-based similarity and the shape-based similarity simultaneously. A mtmerical example is taken to validate the flexibility of the proposed method, and result shows that this method can tackle the uncertainty in real-world supplier selection and also help decision makers to effectively select optimal suppliers.

A Theoretical Explanation of Anomalous Atmospheric Circulation Associated with ENSO Modoki during Boreal Winter

Based on a linear model, the present study provides analytical solutions for ideal triple forcing sources similar to sea surface temperature anomaly （SSTA） pat- terns associated with El Nino-Southern Oscillation （ENSO） Modoki in winter. The ideal triple pattern is composed of an equatorially symmetric heat source in the middle and equatoriaUy asymmetric cold forcing in the southeast and northwest. The equatorially symmetric heat source excites low-level cyclonic circulation anomalies associated with Rossby waves in both hemispheres, while the northwest- ern and southeastern equatorially asymmetric cold sources induce low-level anomalous anticyclones associated with Rossby waves in the hemisphere where the forcing source is located. Low-level zonal winds converge toward the heat sources associated with Kelvin and Rossby waves. Due to unequal forcing intensity in the northwest and southeast, atmospheric responses around the equatorially symmetric forcing become asymmetric, and low-level cyclonic circulation anomalies in the Southern Hemisphere become greater than those in the Northern Hemisphere. Ascending （descending） flows coincide with heat （cold） sources, resulting in a double-cell structure over the regions of forcing sources. Ideal triple patterns similar to SSTA patterns associated with La Nina Modoki produce opposite atmospheric responses. The theoretical atmospheric responses are consistent with observed circulation anomalies associated with ENSO Modoki. Therefore, the theoretical solutions can explain the dynamics responsible for atmospheric circulation anomalies associated with ENSO Modoki events.

Research on the Evolution of Thinking Dynamics Attractor

In this paper we introduce the evolution law of thinking-neural network attractor in the field of thinking dynamics,a new idea about the attractor evolution using evolutional mapping transformation is given on the bases of generalized isologous concept. The idea is connected with the intuitive thinking.This paper lays a foundation for the further studying of the brain thinking process.