James Taylor

Bio: James Taylor is an academic researcher from Newcastle University. The author has contributed to research in topics: Laser & Fiber laser. The author has an hindex of 95, co-authored 1161 publications receiving 39945 citations. Previous affiliations of James Taylor include Institut national de la recherche agronomique & European Spallation Source.

Generation of pulses as short as 93 fs from self-starting femtosecond Cr:LiSrAlF(6) lasers by exploiting multiple-quantum-well absorbers.

Abstract: A Cr:LiSrAIF6 laser has been mode locked by using a multiple-quantum-well (MQW) absorber. With the MQW absorber inside the laser cavity, Kerr lens mode locking is initiated, yielding transform-limited pulses as short as 93 fs. Pulses of 500-fs duration have also been produced by using resonant passive mode locking with the MQW absorber in an external cavity.

Tunable repetition-rate multiplication of a 10 GHz pulse train using linear and nonlinear fiber propagation

Abstract: The temporal Talbot effect and soliton propagation in an optical fiber were exploited to yield a series of pulse train sources with tunable repetition rate simply through variation of the pulse train power in sections of the fiber. In a dual-repetition-rate configuration, 10 and 20 GHz or 10 and 30 GHz repetition rates could be achieved depending on the fiber length used, with pulse durations lower than 21 ps. In a triple-repetition-rate configuration, 10, 20, and 30 GHz repetition rates were obtained, with pulse durations lower than 15 ps.

Direct observation of the multisheet Fermi surface in the strongly correlated transition metal compound ZrZn2.

Abstract: The existence of flat areas of a Fermi surface (FS), predicted by electronic structure calculations and used in models of both magnetically mediated and phonon-mediated Fulde-Ferrell-Larkin-Ovchinnikov superconducting states, is reported in the paramagnetic phase of the ferromagnetic superconductor ZrZn2 using positron annihilation. The strongly mass-renormalized FS sheet, dominating the Fermi level density of states, is seen for the first time. The delocalization of the magnetization is studied using measured and calculated magnetic Compton profiles.

Passive mode locking of a continuous-wave dye laser in the red-near-infrared spectral region

Abstract: Passive mode locking of a cw Rhodamine 700 dye laser is reported for the first time to our knowledge. By using two saturable absorber dyes, DOTCI and HITCI, continuous-output trains of subpicosecond pulses have been obtained in the 727–740- and 762–778-nm spectral regions, respectively. By the addition of a fast-recovery-time dye (DCI) to the DOTCI saturable absorber, pulses as short as 350 fsec at 740 am have been generated.

Sampling for High-Resolution Soil Mapping

Abstract: When doing sensing for high-resolution soil mapping, one has to decide on the disposition of the sensor, which is a special case of spatial sampling. To optimise the pattern of measurements, a cost model and a quality model are proposed. The quality model reflects the coverage of the geographic space, and this is illustrated with some practical experiments. Optimisation of sensing patterns is worked out for two different types of sensing equipment. If the sensor variable differs from the target (management or decision) variable, then a model is needed to predict the target variable from the ancillary data. So in that case, one also has to decide how and where to sample for calibration data. This ‘calibration sampling’ differs from ‘sensor sampling’, as now coverage of the predictor space rather than the geographic space is important. In addition, the handling of extremes is an issue here. Existing methods for calibration sampling are reviewed and a suggestion is made for a new approach, based on fuzzy cluster analysis, which might avoid some of the shortcomings of existing methods.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Using Multivariate Statistics

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The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Linear Matrix Inequalities in System and Control Theory

Abstract: Preface 1. Introduction Overview A Brief History of LMIs in Control Theory Notes on the Style of the Book Origin of the Book 2. Some Standard Problems Involving LMIs. Linear Matrix Inequalities Some Standard Problems Ellipsoid Algorithm Interior-Point Methods Strict and Nonstrict LMIs Miscellaneous Results on Matrix Inequalities Some LMI Problems with Analytic Solutions 3. Some Matrix Problems. Minimizing Condition Number by Scaling Minimizing Condition Number of a Positive-Definite Matrix Minimizing Norm by Scaling Rescaling a Matrix Positive-Definite Matrix Completion Problems Quadratic Approximation of a Polytopic Norm Ellipsoidal Approximation 4. Linear Differential Inclusions. Differential Inclusions Some Specific LDIs Nonlinear System Analysis via LDIs 5. Analysis of LDIs: State Properties. Quadratic Stability Invariant Ellipsoids 6. Analysis of LDIs: Input/Output Properties. Input-to-State Properties State-to-Output Properties Input-to-Output Properties 7. State-Feedback Synthesis for LDIs. Static State-Feedback Controllers State Properties Input-to-State Properties State-to-Output Properties Input-to-Output Properties Observer-Based Controllers for Nonlinear Systems 8. Lure and Multiplier Methods. Analysis of Lure Systems Integral Quadratic Constraints Multipliers for Systems with Unknown Parameters 9. Systems with Multiplicative Noise. Analysis of Systems with Multiplicative Noise State-Feedback Synthesis 10. Miscellaneous Problems. Optimization over an Affine Family of Linear Systems Analysis of Systems with LTI Perturbations Positive Orthant Stabilizability Linear Systems with Delays Interpolation Problems The Inverse Problem of Optimal Control System Realization Problems Multi-Criterion LQG Nonconvex Multi-Criterion Quadratic Problems Notation List of Acronyms Bibliography Index.