Time evolution of the extremely diluted Blume-Emery-Griffiths neural network.

A study of the time evolution and a stability analysis of the phases in the extremely diluted Blume-Emery-Griffiths neural network model are shown to yield new phase diagrams in which fluctuation retrieval may drive pattern retrieval. It is shown that saddle-point solutions associated with fluctuation overlaps slow down the flow of the network states towards the retrieval fixed points. A comparison of the performance with other three-state networks is also presented.

Three-state neural network: from mutual information to the Hamiltonian.

The mutual information, I, of the three-state neural network can be obtained exactly for the mean-field architecture, as a function of three macroscopic parameters: the overlap, the neural activity and the activity-overlap, i.e., the overlap restricted to the active neurons. We perform an expansion of I on the overlap and the activity-overlap, around their values for neurons almost independent of the patterns. From this expansion we obtain an expression for a Hamiltonian which optimizes the retrieval properties of this system. This Hamiltonian has the form of a disordered Blume-Emery-Griffiths model. The dynamics corresponding to this Hamiltonian is found. As a special characteristic of such a network, we see that information can survive even if no overlap is present. Hence the basin of attraction of the patterns and the retrieval capacity is much larger than for the Hopfield network. The extreme diluted version is analyzed, the curves of information are plotted and the phase diagrams are built.

Mutual information of sparsely coded associative memory with self-control and ternary neurons.

The influence of a macroscopic time-dependent threshold on the retrieval dynamics of attractor associative memory models with ternary neurons ¿-1, 0, +1¿ is examined. If the threshold is chosen appropriately as a function of the cross-talk noise and of the activity of the memorized patterns in the model, adapting itself in the course of the time evolution, it guarantees an autonomous functioning of the model. Especially in the limit of sparse coding, it is found that this self-control mechanism considerably improves the quality of the fixed-point retrieval dynamics, in particular the storage capacity, the basins of attraction and the information content. The mutual information is shown to be the relevant parameter to study the retrieval quality of such sparsely coded models. Numerical results confirm these observations.

Categorization in fully connected multistate neural network models.

The categorization ability of fully connected neural network models, with either discrete or continuous Q-state units, is studied in this work in replica symmetric mean-field theory. Hierarchically correlated multistate patterns in a two level structure of ancestors and descendents (examples) are embedded in the network and the categorization task consists in recognizing the ancestors when the network is trained exclusively with their descendents. Explicit results for the dependence of the equilibrium properties of a Q=3-state model and a Q=infinity-state model are obtained in the form of phase diagrams and categorization curves. A strong improvement of the categorization ability is found when the network is trained with examples of low activity. The categorization ability is found to be robust to finite threshold and synaptic noise. The Almeida-Thouless lines that limit the validity of the replica-symmetric results, are also obtained.

[Standardization of an indirect ultramicro ELISA for the determination of total antibodies against the measles virus]. / Estandarización de un sistema ultramicroELISA indirecto para la determinación de anticuerpos totales al virus del sarampión.

An indirect ultramicro ELISA system (UME) for the determination of antibodies to measles virus by the cuban technology of Ultramicro Analytical Systems (SUMA) was developed. A number of 448 serum samples from the National System of Seroepidemiological Surveillance of Measles were simultaneously processed by the Ultramicro ELISA system and by the haemagglutination inhibition technique. Results were compared in both assays. Afterwards; 120 serum pairs obtained from the same source were studies and processed in a similar way. Results evidenced the usefulness of such immunoenzymatic system for the serological diagnosis and the positive validation of replacing conventional techniques by this novel technology.

[Evaluation of an ultramicroELISA system for the diagnosis of rubella]. / Evaluación de un sistema ultramicroELISA para el diagnóstico de la rubéola.

An indirect Ultramicro ELISA assay, previously standardized in our laboratory, for detecting antibodies IgG to the rubella virus was assessed in comparison to the hemagglutination inhibition technique. This assessment allowed to determine its efficacy in the National System for Epidemiological Surveillance of this entity. One hundred and ninety serum pairs of clinically suspected cases of rubella were studied and a high percent of coincidence (99.4%), specificity (99.4%), and sensitivity (100%) was found between both techniques. In addition, 73 serum samples of blood donors were processed using an indirect microELISA system (Berhing) which was compared to the Ultramicro ELISA technique for rubella and it showed a 100% of sensitivity, specificity, and coincidence.

[Applying an ultramicroanalytical system to the diagnosis of infectious diseases]. / Algunas aplicaciones del sistema ultramicroanalítico al diagnóstico de enfermedades infecciosas.

The multiple applications and advantages of the ultramicro analytical system in the serodiagnosis of different diseases produced by viruses, bacteria, and parasites are briefly reported. Also, perspectives in the use of this technology, not only for the diagnosis, but for the detection of microbial antigens are pointed out.