A model of amacrine and ganglion cells for optical information processing

Based on a previously reported logic cell structure (see SPIE, vol. 2038, p. 67-77, 1993), the two types of cells present at the inner and ganglion cell layers of the vertebrate retina and their intracellular response, as well as their connections with each other, have been simulated. These cells are amacrines and ganglion cells. The main scheme of the authors' configuration is shown in a figure. These two types of cells, as well as some of their possible interconnections, have been implemented with the authors' previously reported optical-processing element. As it has been shown, the authors' logic structure is able to process two optical input binary signals, being the output two logical functions. Moreover, if a delayed feedback from one of the two possible outputs to one or both of the inputs is introduced, a very different behaviour is obtained. Depending on the value of the time delay, an oscillatory output can be obtained from a constant optical input signal. Period and length pulses are dependent on delay values, both external and internal, as well as on other control signals. Moreover, a chaotic behaviour can be obtained too under certain conditions

Multiscale object-based classification of satellite images merging multispectral information with panchromatic textural features

Once admitted the advantages of object-based classification compared to pixel-based classification; the need of simple and affordable methods to define and characterize objects to be classified, appears. This paper presents a new methodology for the identification and characterization of objects at different scales, through the integration of spectral information provided by the multispectral image, and textural information from the corresponding panchromatic image. In this way, it has defined a set of objects that yields a simplified representation of the information contained in the two source images. These objects can be characterized by different attributes that allow discriminating between different spectral&textural patterns. This methodology facilitates information processing, from a conceptual and computational point of view. Thus the vectors of attributes defined can be used directly as training pattern input for certain classifiers, as for example artificial neural networks. Growing Cell Structures have been used to classify the merged information.

Training organization of a middle-size company engaged in information technology services: theory and practice

In order to establish an active internal know-how -reserve~ in an information processing and engineering services . company, a training architecture tailored to the company as an whole must be defined. When a company' s earnings come from . advisory services dynamically structured i.n the form of projects, as is the case at hand, difficulties arise that must be taken into account in the architectural design. The first difficulties are of a psychological nature and the design method proposed here begjns wi th the definition of the highest training metasystem, which is aimed at making adjustments for the variety of perceptions of the company's human components, before the architecture can be designed. This approach may be considered as an application of the cybernetic Law of Requisita Variety (Ashby) and of the Principle of Conceptual Integrity (Brooks) . Also included is a description of sorne of the results of the first steps of metasystems at the level of company organization.