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At least 613 records · Page 34Linked to original sources
PubMed2006

Analog neural network for support vector machine learning.

An analog neural network for support vector machine learning is proposed, based on a partially dual formulation of the quadratic programming problem. It results in a simpler circuit implementation with respect to existing neural solutions for the same application. The effectiveness of the proposed network is shown through some computer simulations concerning benchmark problems.

Computers, Analog↗
PubMed1993

A gradient system solution to Potts mean field equations and its electronic implementation.

A gradient system solution method is presented for solving Potts mean field equations for combinatorial optimization problems subject to winner-take-all constraints. In the proposed solution method the optimum solution is searched by using gradient descent differential equations whose trajectory is confined within the feasible solution space of optimization problems. This gradient system is proven theoretically to always produce a legal local optimum solution of combinatorial optimization problems. An elementary analog electronic circuit implementing the presented method is designed on the basis of current-mode subthreshold MOS technologies. The core constituent of the circuit is the winner-take-all circuit developed by Lazzaro et al. Correct functioning of the presented circuit is exemplified with simulations of the circuits implementing the scheme for solving the shortest path problems.

Algorithms↗
PubMed2000

Neural networks in analog hardware--design and implementation issues.

This paper presents a brief review of some analog hardware implementations of neural networks. Several criteria for the classification of general neural networks implementations are discussed and a taxonomy induced by these criteria is presented. The paper also discusses some characteristics of analog implementations as well as some trade-offs and issues identified in the work reviewed. Parameters such as precision, chip area, power consumption, speed and noise susceptibility are discussed in the context of neural implementations. A unified review of various "VLSI friendly" algorithms is also presented. The paper concludes with some conclusions drawn from the analysis of the implementations presented.

Artificial Intelligence↗
PubMed1993

Molecular structures, conformational analysis, and preferential modes of binding of 3-aroyl-2-arylbenzo[b]thiophene estrogen receptor ligands: LY117018 and aryl azide photoaffinity labeling analogs.

Structural and computational modeling studies were performed on the antiestrogen LY117018 (3) and two photoaffinity labeling analogs, in which an azide replaces the basic ether side chain (methyl ether tetrafluoro azide 7 and its protio analog 8). These studies were undertaken in order to determine the conformational preferences of these compounds and to propose favorable orientational modes for their binding to the estrogen receptor. In the crystallographic studies, we found that, unlike tetrafluoro azide 7, which adopts a face-to-face stacking of the p-hydroxyphenyl and benzoyl groups in the solid state, the pendant rings in the corresponding protio analog 8 are found in a predominantly offset pi-stacked array. In LY117018, which has an ether on the benzoyl ring, stacking of the pendant rings does not occur in the crystal structure; it assumes a T-shape, with the benzoyl group oriented perpendicular to the benzo[b]thiophene nucleus. In modeling studies, analogs of LY117018, 7, and 8 were subjected to a conformational grid search by molecular mechanics, and for each compound, three low-energy conformers (and their atropisomers) were obtained. These conformers were further geometry optimized by semiempirical molecular orbital calculations. For each compound, one of the three minimum-energy conformers is quite similar to the solid-state geometry. The computational structure of the tetrafluoro azide showed the greatest stacking between the benzoyl group and the p-methoxyphenyl ring, but less stacking than was observed in the crystallographic structure. The orientational preferences of these benzo[b]thiophene ligands with the estrogen receptor were analyzed with the receptor volume mapping technique, a method based on the correspondence of the hydroxyl groups and the volume that the benzo[b]thiophene compound shares with a composite molecular volume of high-affinity estradiol-type ligands (the receptor excluded volume, RExV). If the benzo[b]thiophene nucleus is overlapped with the steroid AB rings, the best overlap with the RExV is achieved, but there is poor correspondence of the hydroxyl groups. An orientation and conformation in which the benzoyl group of the 3-benzoyl-2-aryl-benzo[b]thiophenes occupies a 7 alpha-like position relative to the steroid produces both ample volume overlap with the RExV and close approximation of the hydroxyl groups and is presented as the putative bioactive conformation.

Affinity Labels↗
PubMed1994

ACT3: a high-speed, high-precision electrical impedance tomograph.

This paper presents the design, implementation, and performance of Rensselaer's third-generation Adaptive Current Tomograph, ACT3. This system uses 32 current sources and 32 phase-sensitive voltmeters to make a 32-electrode system that is capable of applying arbitrary spatial patterns of current. The instrumentation provides 16 b precision on both the current values and the real and reactive voltage readings and can collect the data for a single image in 133 ms. Additionally, the instrument is able to automatically calibrate its voltmeters and current sources and adjust the current source output impedance under computer control. The major system components are discussed in detail and performance results are given. Images obtained using stationary agar targets and a moving pendulum in a phantom as well as in vivo resistivity profiles showing human respiration are shown.

Algorithms↗
PubMed1999

Neural mechanisms for processing binocular information II. Complex cells.

Complex cells in the striate cortex exhibit extensive spatiotemporal nonlinearities, presumably due to a convergence of various subunits. Because these subunits essentially determine many aspects of a complex cell receptive field (RF), such as tuning for orientation, spatial frequency, and binocular disparity, examination of the RF properties of subunits is important for understanding functional roles of complex cells. Although monocular aspects of these subunits have been studied, little is known about their binocular properties. Using a sophisticated RF mapping technique that employs binary m-sequences, we have examined binocular interactions exhibited by complex cells in the cat's striate cortex and the binocular RF properties of their underlying functional subunits. We find that binocular interaction RFs of complex cells exhibit subregions that are elongated along the frontoparallel axis at different binocular disparities. Therefore responses of complex cells are largely independent of monocular stimulus position or phase as long as the binocular disparity of the stimulus is kept constant. The binocular interaction RF is well described by a sum of binocular interaction RFs of underlying functional subunits, which exhibit simple cell-like RFs and a preference for different monocular phases but the same binocular disparity. For more than half of the complex cells examined, subunits of each cell are consistent with the characteristics specified by an energy model, with respect to the number of subunits as well as relationships between the subunit properties. Subunits exhibit RF binocular disparities that are largely consistent with a phase mechanism for encoding binocular disparity. These results indicate that binocular interactions of complex cells are derived from simple cell-like subunits, which exhibit multiplicative binocular interactions. Therefore binocular interactions of complex cells are also multiplicative. This suggests that complex cells compute something analogous to an interocular cross-correlation of images for a local region of visual space. The result of this computation can be used for solving the stereo correspondence problem.

Animals↗
PubMed1978

The use of computers in pharmacokinetics.

A review of computer applications is presented, and several examples of the use of analog and digital computers are given. Special attention is given to fitting the time concentration data to the one, two or more exponential equations, for estimation of pharmacokinetic parameters, for dosage regimen of drugs and for evaluation of bioavailability.

Biological Availability↗