I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Digital filters can be broadly classified into two groups: recursive (infinite impulse response (IIR)) and non-recursive (finite impulse response (FIR)). An IIR filter can provide a much better performance than the FIR filter having the same number of coefficients. However, IIR filters might have a multi-modal error surface. Therefore, a reliable design method proposed for IIR filters must be based on a global search procedure. Artificial bee colony (ABC) algorithm has been recently introduced for global optimization. The ABC algorithm simulating the intelligent foraging behaviour of honey bee swarm is a simple, robust, and very flexible algorithm. In this work, a new method based on ABC algorithm for designing digital IIR filters is described and its performance is compared with that of a conventional optimization algorithm (LSQ-nonlin) and particle swarm optimization (PSO) algorithm.

/pdf/a-new-design-method-based-on-artificial-bee-colony-algorithm-4h83c1feyi.pdf

A new design method based on artificial bee colony algorithm for digital IIR filters

Although the off-road mobility characteristics of wheeled or tracked vehicles are generally recognized as being inferior to those of man and cursorial animals, the complexity of the joint-coordination control problem has thus far frustrated attempts to achieve improved vehicular terrain adaptability through the application of legged locomotion concepts. Nevertheless, the evident superiority of biological systems in this regard has motivated a number of theoretical studies over the past decade which have now reached a state of maturity sufficient to permit the construction of experimental computer-controlled adaptive walking machines. At least two such vehicles are known to have recently demonstrated legged locomotion over smooth hard-surfaced terrain. This paper is concerned with an extension of the present theory of limb coordination for such machines to the case in which the terrain includes regions not suitable for weight-bearing and which must consequently be avoided by the control computer in deciding when and where to successively place the feet of the vehicle. The paper includes a complete problem formalization, a heuristic algorithm for solution of the problem thus posed, and a preliminary evaluation of the proposed algorithm in terms of a computer simulation study.

Adaptive Locomition of a Multilegged Robot over Rough Terrain

Introduction to stochastic control

Since the error surface of digital infinite-impulse-response (IIR) filters is generally nonlinear and multimodal, global optimization techniques are required in order to avoid local minima. In this paper, a seeker-optimization-algorithm (SOA)-based evolutionary method is proposed for digital IIR filter design. SOA is based on the concept of simulating the act of human searching in which the search direction is based on the empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. The algorithm's performance is studied with comparison of three versions of differential evolution algorithms, four versions of particle swarm optimization algorithms, and genetic algorithm. The simulation results show that SOA is superior or comparable to the other algorithms for the employed examples and can be efficiently used for IIR filter design.

Seeker Optimization Algorithm for Digital IIR Filter Design

https://eprints.soton.ac.uk/261519/1/sdarticle.pdf

Intelligent legged climbing service robot for remote maintenance applications in hazardous environments

Adaptive infinite-impulse-response (IIR) filtering provides a powerful approach for solving a variety of practical signal processing problems. Because the error surface of IIR filters is typically multimodal, global optimisation techniques are generally required in order to avoid local minima. This contribution applies the particle swarm optimisation (PSO) to digital IIR filter design in a realistic time domain setting where the desired filter output is corrupted by noise. PSO as global optimisation techniques offers advantages of simplicity in implementation, ability to quickly converge to a reasonably good solution and robustness against local minima. Our simulation study involving system identification application confirms that the proposed approach is accurate and has a fast convergence rate and the results obtained demonstrate that the PSO offers a viable tool to design digital IIR filters. We also apply the quantum-behaved particle swarm optimisation (QPSO) algorithm to the same digital IIR filter design and our results do not show any performance advantage of the QPSO algorithm over the PSO, although the former does have fewer algorithmic parameters that require tuning.

/pdf/digital-iir-filter-design-using-particle-swarm-optimisation-3v4y1nm221.pdf

Digital IIR filter design using particle swarm optimisation

Digital IIR Filter Design Using Adaptive Simulated Annealing

Purpose – Aims to report on the various types of tele‐operated mobile service robots for remote inspection and maintenance, especially in the field of nuclear industry.Design/methodology/approach – Describes nuclear electric robot operator (NERO), Sizewell A duct inspection equipment (SADIE), Robug‐IIs (all leg‐based) and Roboslave (wheel‐based).Findings – That these robots can handle a significant portion of inspection and maintenance tasks in a typical nuclear plant, though, given that they are primarily tailor‐made, they are still too expensive for ordinary industries.Originality/value – As the interests of health and safety and paramount, this study sees the use of such robots expanding and diversifying, irrespective of cost.

/pdf/tele-operated-climbing-and-mobile-service-robots-for-remote-9q5vxwb459.pdf

Tele‐operated climbing and mobile service robots for remote inspection and maintenance in nuclear industry

Nuclear reactor pressure vessels are often required regular inspection and maintenance in order to ensure the safety of the reactors. Failing to carry out proper maintenance could cause severe casualty. The usual way of carrying out inspection in these hazardous environments is using long reach fixed base manipulators. However, these manipulators suffer from low payload capacity and relatively large end point deflections. Also, the installation and the storage of these long manipulators could be costly. An alternative solution is to use walking-climbing robots, which overcome the problems encountered by the long reach manipulators. In this paper, two robots, NERO (Nuclear Electric Robot Operator) and SADIE (Sizewell A Duct Inspection Equipment) which have been applied successfully to inspect two Magnox reactors in the UK are described. The deployment and operational experience of these robots are also explained. Finally the applications and the usefulness of these robots for improving safety inspection of nuclear reactors in general are discussed in this paper.

https://journals.sagepub.com/doi/pdf/10.1177/002029400603900201

B.L. Luk

Papers

Intelligent legged climbing service robot for remote maintenance applications in hazardous environments

Digital IIR filter design using particle swarm optimisation

Digital IIR Filter Design Using Adaptive Simulated Annealing

Tele‐operated climbing and mobile service robots for remote inspection and maintenance in nuclear industry

Walking and climbing service robots for safety inspection of nuclear reactor pressure vessels