Kybernetes

James G. Wilson; Richard J. Mitchell

2000 Kybernetes

doi: 10.1108/03684920010308835

This paper describes the novel use of agent and cellular neural Hopfield network techniques in the design of a self‐contained, object detecting retina. The agents, which are used to detect features within an image, are trained using the Hebbian method which has been modified for the cellular architecture. The success of each agent is communicated with adjacent agents in order to verify the detection of an object. Initial work used the method to process bipolar images. This has now been extended to handle grey scale images. Simulations have demonstrated the success of the method and further work is planned in which the device is to be implemented in hardware.

Shoucheng Ou Yang; Jinghai Miao; Yong Wu; Yi Lin; Taoyong Peng; Tiangui Xiao

2000 Kybernetes

doi: 10.1108/03684920010308853

Based on the summary and analysis of the particle dynamics, developed in the past 300 years, and of fundamental properties of unevenness of natural materials, we propose the opinion of the second stir. We analyze the gains and loses of employing the non‐dimensionalization method developed in the quantitative analysis system of the first push. Combined with some theoretical models, we also consider the epistemological failures of pure quantification, linearization, and formal logic analysis.

A. Ziadi; Y. Cherruault

2000 Kybernetes

doi: 10.1108/03684920010308871

The reducing transformation and global optimization technique called Alienor has been developed in the 1980s by Cherruault and Guillez. These methods are based on the approximating properties of ॅ ‐dense curves. The aim of this work is to give a very large class of functions generating ॅ ‐dense curves in a hyper‐rectangle of R n .

Ralf Östermark

2000 Kybernetes

doi: 10.1108/03684920010308862

The performance of Aoki’s state space algorithm and the Cartesian ARIMA search algorithm (CARlMA) of Östermark and Höglund is compared. The analysis is carried out on a set of stock prices on the Helsinki (Finland) and Stockholm (Sweden) Stock Exchanges. Demonstrates that the Finnish and Swedish stock markets differ in predictability of stock prices. With Finnish stock data, Aoki’s state space algorithm outperforms the subset of MAPE minimizing forecasts. In contrast, with Swedish stock data, ARIMA‐models of a fairly simple structure outperform Aoki’s algorithm. The stock markets are seen to differ in complexity of time series models as well as in predictability of individual asset prices.

Janusz Bucki; Yvon Pesqueux

2000 Kybernetes

doi: 10.1108/03684920010308880

Companies are becoming more and more dependent on data processing systems. In this context, cybernetics again finds its meaning dealing with man‐machine communication problems. The two professions (data‐processing and management) have to find an answer to the same question: how to present a model of a company as a complex system? Decision system analysis follows this trend and suggests a set of concepts and approaches that allows us to analyze and conceive complex systems, whether they be human organizations or systems of artefacts. Despite the fact that it belongs to the cybernetic trend of thinking, the analysis integrates such notions as culture, creativity, well‐being, goals, real time, suggesting a more complete vision of these aspects starting from a logical deductive model, to a renewed cybernetic vision.

Henri Berliocchi

2000 Kybernetes

doi: 10.1108/03684920010308899

A protocol showing the ॆ − activity of high dilutions of nitric acid is described. It is given a physical mathematical frame founded on a an approach of quantum relativistic field based on the theory of Solovay (ethers theory, remanent wave).