Refinamiento de la estructura tridimensional de macromoléculas biológicas aisladas: Principios y realización en multiprocesadores

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Escuela Técnica Superior de Informática, Departamento de Ingeniería Informática. Fecha de lectura: 12-03-1998

Differential Evolution under Fixed Point Arithmetic and FP16 Numbers

In this work, the differential evolution algorithm behavior under a fixed point arithmetic is analyzed also using half-precision floating point (FP) numbers of 16 bits, and these last numbers are known as FP16. In this paper, it is considered that it is important to analyze differential evolution (DE) in these circumstances with the goal of reducing its consumption power, storage size of the variables, and improve its speed behavior. All these aspects become important if one needs to design a dedicated hardware, as an embedded DE within a circuit chip, that performs optimization. With these conditions DE is tested using three common multimodal benchmark functions: Rosenbrock, Rastrigin, and Ackley, in 10 dimensions. Results are obtained in software by simulating all numbers using C programming language

Generating Even More Chaotic Instances in Hardware

It is well known that multiplication inside a computer does not follow the associative property because of roundoff effects. It is possible to use this fact to generate other different chaotic instances of chaotic maps or oscillators when a multiplication of three terms appears. Chaos is very sensitive to small changes in the initial conditions and amplifies these small rounding effects. We use this condition to build different chaotic instances, which give different results, of the Lü oscillator and the 2D map, and we show one application to create new instances of a pseudo random number generator using the 2D map. Both chaotic systems are simulated in software and in hardware within an FPGA where another 144 different 2D map instances and 81 different Lü oscillators can be created. To best of our knowledge, it is the first paper that analyze the construction of new chaotic entities by using the roundoff effects

Optimizing the Maximal Perturbation in Point Sets while Preserving the Order Type

Recently a new kind of fiducial marker based on order type (OT) has been proposed. Using OT one can unequivocally identify a set of points through its triples of point orientation, and therefore, there is no need to use metric information. These proposed order type tags (OTTs) are invariant under a projective transformation which allows identification of them directly from a photograph. The magnitude of noise in the point positions that a set of points can support without changing its OT, is named the maximal perturbation (MP) value. This value represents the maximal displacement that any point in the set can have in any direction without changing the triplet’s orientation in the set. A higher value of the MP makes an OTT instance more robust to perturbations in the points positions. In this paper, we address the problem of how to improve the MP value for sets of points. We optimize “by hand” the MP for all the 16 subsets of points in the set of OTs composed of six points, and we also propose a general algorithm to optimize all the sets of OTs composed of six, seven, and eight points. Finally, we show several OTTs with improved MP values, and their use in an augmented reality application

Confidence limits for resolution estimation in image averaging by random subsampling

In this communication we present an empirical approach to the task of estimating the reproducible limit of resolution that can be achieved when a set of images is averaged. The proposed solution is based on a random subsampling method. We derive confidence limits for two of the most widely used measures of reproducibility in this field, the differential phase residual (DPR) and the Fourier ring correlation (FRC). Results both for negatively stained specimens and for those embedded in ice are presented. Our results provide a common framework that allows a number of previous observations and suggestions regarding these measures to be further analyzed.Comisión Internacional de Ciencia y Tecnología (España)This work has been partly supported by grant PB91-0910 and BI0950768 from the Comision Intermenisterial de Ciencia y Tecnologia, Spain. Mr. L.G. de la Fraga holds a Mutis predoctoral studenship granted by Instituto de Cooperation Ibero Americana. Dr. J. Dopazo holds a postdoctoral contract granted by Fundacion Ramon Areces-CSIC.Peer reviewe

Engineering applications of fpgas: chaotic systems, artificial neural networks, random number generators, and secure communication systems

This book offers readers a clear guide to implementing engineering applications with FPGAs, from the mathematical description to the hardware synthesis, including discussion of VHDL programming and co-simulation issues. Coverage includes FPGA realizations such as: chaos generators that are described from their mathematical models; artificial neural networks (ANNs) to predict chaotic time series, for which a discussion of different ANN topologies is included, with different learning techniques and activation functions; random number generators (RNGs) that are realized using different chaos generators, and discussions of their maximum Lyapunov exponent values and entropies. Finally, optimized chaotic oscillators are synchronized and realized to implement a secure communication system that processes black and white and grey-scale images. In each application, readers will find VHDL programming guidelines and computer arithmetic issues, along with co-simulation examples with Active-HDL and Simulink. Readers will benefit from this practical guide to implementing a variety of engineering applications from VHDL programming and co-simulation issues, to FPGA realizations of chaos generators, ANNs for chaotic time-series prediction, RNGs and chaotic secure communications for image transmission

On the Sizing of CMOS Operational Amplifiers by Applying Many-Objective Optimization Algorithms

In CMOS integrated circuit (IC) design, operational amplifiers are one of the most useful active devices to enhance applications in analog signal processing, signal conditioning and so on. However, due to the CMOS technology downscaling, along the very large number of design variables and their trade-offs, it results difficult to reach target specifications without the application of optimization methods. For this reason, this work shows the advantages of performing many-objective optimization and this algorithm is compared to the well-known mono- and multi-objective metaheuristics, which have demonstrated their usefulness in sizing CMOS ICs. Three CMOS operational transconductance amplifiers are the case study in this work; they were sized by applying mono-, multi- and many-objective algorithms. The well-known non-dominated sorting genetic algorithm version 3 (NSGA-III) and the many-objective metaheuristic-based on the R2 indicator (MOMBI-II) were applied to size CMOS amplifiers and their sized solutions were compared to mono- and multi-objective algorithms. The CMOS amplifiers were optimized considering five targets, associated to a figure of merit (FoM), differential gain, power consumption, common-mode rejection ratio and total silicon area. The designs were performed using UMC 180 nm CMOS technology. To show the advantage of applying many-objective optimization algorithms to size CMOS amplifiers, the amplifier with the best performance was used to design a fractional-order integrator based on OTA-C filters. A variation analysis considering the process, the voltage and temperature (PVT) and a Monte Carlo analysis were performed to verify design robustness. Finally, the OTA-based fractional-order integrator was used to design a fractional-order chaotic oscillator, showing good agreement between numerical and SPICE simulations

Estimating the Highest Time-Step in Numerical Methods to Enhance the Optimization of Chaotic Oscillators

The execution time that takes to perform numerical simulation of a chaotic oscillator mainly depends on the time-step h. This paper shows that the optimization of chaotic oscillators can be enhanced by estimating the highest h in either one-step or multi-step methods. Four chaotic oscillators are used as a case study, and the optimization of their Kaplan-Yorke dimension (DKY) is performed by applying three metaheuristics, namely: particle swarm optimization (PSO), many optimizing liaison (MOL), and differential evolution (DE) algorithms. Three representative one-step and three multi-step methods are used to solve the four chaotic oscillators, for which the estimation of the highest h is obtained from their stability analysis. The optimization results show the effectiveness of using a high h value for the six numerical methods in reducing execution time while maximizing the positive Lyapunov exponent (LE+) and DKY of the chaotic oscillators by applying PSO, MOL, and DE algorithms