Genetic adaptive state estimation

A genetic algorithm (GA) uses the principles of evolution, natural selection, and genetics to offer a method for parallel search of complex spaces. This paper describes a GA that can perform on-line adaptive state estimation for linear and nonlinear systems. First, it shows how to construct a genetic adaptive state estimator where a GA evolves the model in a state estimator in real time so that the state estimation error is driven to zero. Next, several examples are used to illustrate the operation and performance of the genetic adaptive state estimator. Its performance is compared to that of the conventional adaptive Luenberger observer for two linear system examples. Next, a genetic adaptive state estimator is used to predict when surge and stall occur in a nonlinear jet engine. Our main conclusion is that the genetic adaptive state estimator has the potential to offer higher performance estimators for nonlinear systems over current methods.     

A new criterion of delay-dependent asymptotic stability for Hopfield neural networks with time delay.

In this brief, the problem of global asymptotic stability for delayed Hopfield neural networks (HNNs) is investigated. A new criterion of asymptotic stability is derived by introducing a new kind of Lyapunov-Krasovskii functional and is formulated in terms of a linear matrix inequality (LMI), which can be readily solved via standard software. This new criterion based on a delay fractioning approach proves to be much less conservative and the conservatism could be notably reduced by thinning the delay fractioning. An example is provided to show the effectiveness and the advantage of the proposed result.     

Evaluation of amplitude-based sorting algorithm to reduce lung tumor blurring in PET images using 4D NCAT phantom

PURPOSE: develop and validate a PET sorting algorithm based on the respiratory amplitude to correct for abnormal respiratory cycles. METHOD AND MATERIALS: using the 4D NCAT phantom model, 3D PET images were simulated in lung and other structures at different times within a respiratory cycle and noise was added. To validate the amplitude binning algorithm, NCAT phantom was used to simulate one case of five different respiratory periods and another case of five respiratory periods alone with five respiratory amplitudes. Comparison was performed for gated and un-gated images and for the new amplitude binning algorithm with the time binning algorithm by calculating the mean number of counts in the ROI (region of interest). RESULTS: an average of 8.87+/-5.10% improvement was reported for total 16 tumors with different tumor sizes and different T/B (tumor to background) ratios using the new sorting algorithm. As both the T/B ratio and tumor size decreases, image degradation due to respiration increases. The greater benefit for smaller diameter tumor and lower T/B ratio indicates a potential improvement in detecting more problematic tumors.     

The relation between color discrimination and color constancy: when is optimal adaptation task dependent?

Color vision supports two distinct visual functions: discrimination and constancy. Discrimination requires that the visual response to distinct objects within a scene be different. Constancy requires that the visual response to any object be the same across scenes. Across changes in scene, adaptation can improve discrimination by optimizing the use of the available response range. Similarly, adaptation can improve constancy by stabilizing the visual response to any fixed object across changes in illumination. Can common mechanisms of adaptation achieve these two goals simultaneously? We develop a theoretical framework for answering this question and present several example calculations. In the examples studied, the answer is largely yes when the change of scene consists of a change in illumination and considerably less so when the change of scene consists of a change in the statistical ensemble of surface reflectances in the environment.     

Constructive Membership Predicates as Index Types

In the constructive setting, membership predicates over recursive types are inhabited by terms indexing the elements that satisfy the criteria for membership. In this paper, we motivate and explore this idea in the concrete setting of lists and trees. We show that the inhabitants of membership predicates are precisely the inhabitants of a generic shape type. We show that membership of x (of type T) in structure S, (x_TS) can not, in general, index all parts of a structure S and we generalize to a form ρS where ρ is a predicate over S. Under this scheme, (λx.True)S is the set of all indexes into S, but we show that not all subsets of indexes are expressible by strictly local predicates. Accordingly, we extend our membership predicates to predicates that retain state “from above” as well as allow “looking below”. Predicates of this form are complete in the sense that they can express every subset of indexes in S. These ideas are motivated by experience programming in Nuprl's constructive type theory and examining the constructive content of mechanically checked formal proofs involving membership predicates.     

BPL: A set-based language for distributed system prototyping

Rapid prototyping of software and hardware is recognized as a very important step in timely, cost-effective system development. The complexity inherent in designing distributed computing systems and distributed problem solutions emphasizes the need for effective rapid prototyping tools. ADL/ADS is a testbed user interface tool for experimentation with critical research and design issues pertaining to distributed data processing (DDP). The experimenter expresses a candidate distributed system in terms of experiment objects, along with attributes and relationships. The experiment objects represent hardware, software, and behavior. This paper provides a brief overview of ADL/ADS, and gives especial emphasis to the Behavior Prototyping Language (BPL) within ADL/ADS. BPL is designed for expressing Behavior Modules (B_MODULEs)—the most versatile of the behavior objects. BPL incorporates set-theoretical approaches, and provides syntax designed for effectively describing manipulations of experiment objects, and their attributes and relationships.     

Locations considered unnecessary

Summary Recent papers have attacked the use of locations, or pointers, as data objects in programs. This paper considers a generalization of this attack — attempting to remove locations from the underlying semantic model. Using the mathematical semantics of Scott and Strachey, we show that reference parameters and Algol scope rules for procedures, two constructs requiring the notion of reference, can be replaced with alternative constructs not requiring locations in the definition. Some conclusions are also drawn about the use of mathematical semantics as a language design tool.This research was partially supported by the National Research Council of Canada and by National Science Foundation grant MCS 76-14293