Quantization effects in digitally behaving circuit implementationsof Kohonen networks

Implementing a neural network on a digital or mixed analog and digital chip yields the quantization of the synaptic weights dynamics. This paper addresses this topic in the case of Kohonen's self-organizing maps. We first study qualitatively how the quantization affects the convergence and the properties, and deduce from this analysis the way to choose the parameters of the network (adaptation gain and neighborhood). We show that a spatially decreasing neighborhood function is far more preferable than the usually rectangular neighborhood function, because of the weight quantization. Based on these results, an analog nonlinear network, integrated in a standard CMOS technology, and implementing this spatially decreasing neighborhood function is then presented. It can be used in a mixed analog and digital circuit implementation.     

An object-oriented query evaluation scheme for logical databases inmassively parallel environment

Taking advantage of the structure of logical representations, we report an algorithm that evaluates conjunctive queries in a massively parallel environment under an object-based representation for deductive databases. By distributing objects in a database, we show that parallel evaluation of a query can be achieved in a cooperative way so that the conventional tuple-by-tuple, operation-by-operation evaluation strategy can be replaced by a global, parallel matching approach. With the proposed scheme, all conjuncts of a given query can be examined at the same time, which enables us to eliminate the need of any temporary relation. On the other hand, compared with the interpretive method, we show that any data dependency imposed by shared variables is no longer a major problem in achieving AND-parallelism by the proposed scheme     

An algebraic theory of object-oriented systems

The paper presents an algebraic specification of net objects. By net objects we mean those that are defined in object-oriented paradigms and those defined with nested relations in complex database models. An algebraic specification is set up that involves structures of net objects, accesses of net objects, and some features of object-oriented programming, such as multiple inheritance and polymorphism. Objects and their relationships are then characterized formally in the modeling, which utilizes the hierarchical approach in the algebraic theory of abstract data types, and is further developed by adding mechanisms from existing object systems. Categories of net objects are presented with the properties of accesses among them     

Temporal specialization and generalization

A standard relation has two dimensions: attributes and tuples. A temporal relation contains two additional orthogonal time dimensions: valid time records when facts are true in the modeled reality, and transaction time records when facts are stored in the temporal relation. Although there are no restrictions between the valid time and transaction time associated with each fact, in many practical applications the valid and transaction times exhibit restricted interrelationships that define several types of specialized temporal relations. This paper examines areas where different specialized temporal relations are present. In application systems with multiple, interconnected temporal relations, multiple time dimensions may be associated with facts as they flow from one temporal relation to another. The paper investigates several aspects of the resulting generalized temporal relations, including the ability to query a predecessor relation from a successor relation. The presented framework for generalization and specialization allows one to precisely characterize and compare temporal relations and the application systems in which they are embedded. The framework's comprehensiveness and its use in understanding temporal relations are demonstrated by placing previously proposed temporal data models within the framework. The practical relevance of the defined specializations and generalizations is illustrated by sample realistic applications in which they occur. The additional semantics of specialized relations are especially useful for improving the performance of query processing     

Structuring fault-tolerant object systems for modularity in adistributed environment

The object-oriented approach to system structuring has found widespread acceptance among designers and developers of robust computing systems. The authors propose a system structure for distributed programming systems that support persistent objects and describe how properties such as persistence and recoverability can be implemented. The proposed structure is modular, permitting easy exploitation of any distributed computing facilities provided by the underlying system. An existing system constructed according to the principles espoused here is examined to illustrate the practical utility of the proposed approach to system structuring     

On the performance of synchronized programs in distributed networkswith random processing times and transmission delays

A synchronizer is a compiler that transforms a program designed to run in a synchronous network into a program that runs in an asynchronous network. The behavior of a simple synchronizer, which also represents a basic mechanism for distributed computing and for the analysis of marked graphs, was studied by S. Even and S. Rajsbaum (1990) under the assumption that message transmission delays and processing times are constant. We study the behavior of the simple synchronizer when processing times and transmission delays are random. The main performance measure is the rate of a network, i.e., the average number of computational steps executed by a processor in the network per unit time. We analyze the effect of the topology and the probability distributions of the random variables on the behavior of the network. For random variables with exponential distribution, we provide tight (i.e., attainable) bounds and study the effect of a bottleneck processor on the rate     

Using recurrent neural networks for adaptive communication channelequalization

Nonlinear adaptive filters based on a variety of neural network models have been used successfully for system identification and noise-cancellation in a wide class of applications. An important problem in data communications is that of channel equalization, i.e., the removal of interferences introduced by linear or nonlinear message corrupting mechanisms, so that the originally transmitted symbols can be recovered correctly at the receiver. In this paper we introduce an adaptive recurrent neural network (RNN) based equalizer whose small size and high performance makes it suitable for high-speed channel equalization. We propose RNN based structures for both trained adaptation and blind equalization, and we evaluate their performance via extensive simulations for a variety of signal modulations and communication channel models. It is shown that the RNN equalizers have comparable performance with traditional linear filter based equalizers when the channel interferences are relatively mild, and that they outperform them by several orders of magnitude when either the channel's transfer function has spectral nulls or severe nonlinear distortion is present. In addition, the small-size RNN equalizers, being essentially generalized IIR filters, are shown to outperform multilayer perceptron equalizers of larger computational complexity in linear and nonlinear channel equalization cases.     

Connectivity and performance tradeoffs in the cascade correlationlearning architecture

The cascade correlation is a very flexible, efficient and fast algorithm for supervised learning. It incrementally builds the network by adding hidden units one at a time, until the desired input/output mapping is achieved. It connects all the previously installed units to the new unit being added. Consequently, each new unit in effect adds a new layer and the fan-in of the hidden and output units keeps on increasing as more units get added. The resulting structure could be hard to implement in VLSI, because the connections are irregular and the fan-in is unbounded. Moreover, the depth or the propagation delay through the resulting network is directly proportional to the number of units and can be excessive. We have modified the algorithm to generate networks with restricted fan-in and small depth (propagation delay) by controlling the connectivity. Our results reveal that there is a tradeoff between connectivity and other performance attributes like depth, total number of independent parameters, and learning time.     

Fixed-order H∞ compensator design

A method is presented for the construction of fixed-order compensators to provide H_∞ norm constraint for linear control systems with exogenous disturbances. The method is based on the celebrated bounded-real lemma that predicates the H_∞ norm constraint via a Riccati inequality. The synthesis of fixed-order controllers whose dimensions are less than the order of a given plant, is demonstrated by a set of sufficient conditions along with a numerical algorithm.     

The design, fabrication, and testing of corrugated silicon nitridediaphragms

Silicon nitride corrugated diaphragms of 2 mm×2 mm×1 μm have been fabricated with 8 circular corrugations, having depths of 4, 10, or 14 μm. The diaphragms with 4-μm-deep corrugations show a measured mechanical sensitivity (increase in the deflection over the increase in the applied pressure) which is 25 times larger than the mechanical sensitivity of flat diaphragms of equal size and thickness. Since this gain in sensitivity is due to reduction of the initial stress, the sensitivity can only increase in the case of diaphragms with initial stress. A simple analytical model has been proposed that takes the influence of initial tensile stress into account. The model predicts that the presence of corrugations increases the sensitivity of the diaphragms, because the initial diaphragm stress is reduced. The model also predicts that for corrugations with a larger depth the sensitivity decreases, because the bending stiffness of the corrugations then becomes dominant. These predictions have been confirmed by experiments. The application of corrugated diaphragms offers the possibility to control the sensitivity of thin diaphragms by geometrical parameters, thus eliminating the effect of variations in the initial stress, due to variations in the diaphragm deposition process and/or the influence of temperature changes and packaging stress