A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators

/pdf/handbook-of-fingerprint-recognition-16mh887j24.pdf

Handbook of Fingerprint Recognition

Forecasting with artificial neural networks: the state of the art

A review and tutorial of the fundamental ideas and methods of joint time-frequency distributions is presented. The objective of the field is to describe how the spectral content of a signal changes in time and to develop the physical and mathematical ideas needed to understand what a time-varying spectrum is. The basic gal is to devise a distribution that represents the energy or intensity of a signal simultaneously in time and frequency. Although the basic notions have been developing steadily over the last 40 years, there have recently been significant advances. This review is intended to be understandable to the nonspecialist with emphasis on the diversity of concepts and motivations that have gone into the formation of the field. >

/pdf/time-frequency-distributions-a-review-3lxbcw4fg4.pdf

Time-frequency distributions-a review

1980 Preface * 1999 Preface * 1999 Acknowledgements * Introduction * 1 Circular Logic * 2 Phase Singularities (Screwy Results of Circular Logic) * 3 The Rules of the Ring * 4 Ring Populations * 5 Getting Off the Ring * 6 Attracting Cycles and Isochrons * 7 Measuring the Trajectories of a Circadian Clock * 8 Populations of Attractor Cycle Oscillators * 9 Excitable Kinetics and Excitable Media * 10 The Varieties of Phaseless Experience: In Which the Geometrical Orderliness of Rhythmic Organization Breaks Down in Diverse Ways * 11 The Firefly Machine 12 Energy Metabolism in Cells * 13 The Malonic Acid Reagent ('Sodium Geometrate') * 14 Electrical Rhythmicity and Excitability in Cell Membranes * 15 The Aggregation of Slime Mold Amoebae * 16 Numerical Organizing Centers * 17 Electrical Singular Filaments in the Heart Wall * 18 Pattern Formation in the Fungi * 19 Circadian Rhythms in General * 20 The Circadian Clocks of Insect Eclosion * 21 The Flower of Kalanchoe * 22 The Cell Mitotic Cycle * 23 The Female Cycle * References * Index of Names * Index of Subjects

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/596B270197FE27DE5FABB598B6210622/S0025557200150892a.pdf/div-class-title-span-class-italic-the-geometry-of-biological-time-span-by-a-t-winfree-pp-544-dm68-corrected-second-printing-1990-isbn-3-540-52528-9-springer-div.pdf

The geometry of biological time , by A. T. Winfree. Pp 544. DM68. Corrected Second Printing 1990. ISBN 3-540-52528-9 (Springer)

The organization of behavior: A neuropsychological theory

While Oja et al. have derived a Hebbian learning neural net algorithm of PCA reproducing Petland's eigenfaces for examples, Bell-Sejnowski and Amari have improved an unsupervised maximum output entropy learning algorithm for ICA sensory pre-processing reproducing the Hubel-Wiesel edge maps, among others. This paper unifies proofs of the convergence of both supervised and unsupervised learning artificial neural networks in the Lyapunov sense. It implies the effortless division of labor such as the cocktail party effect of supervised word spotting under the unsupervised rejection of severe clutter noise. The proof is based on the minimization of Helmholtz thermodynamic free energy: A=U -TS; Hopfield dynamics: du/sub i//dt=-/spl part/U(v/sub i/)//spl part/v/sub i/; v/sub i/=/spl sigma/o(u/sub i/); and Bell-Sejnowski dynamics: du/sub i//dt=+/spl part/S(w/sub ij/)//spl part/w/sub ij/ for arbitrary brain-like open systems which suggests homeostasis constant body temperature T reservoir. This is characteristic of all mammals, as opposed to cold-blooded reptiles. Other than the known cocktail party effect, applications are given to unsupervised image de-noise generalization of PCA eigenfaces and the supervised recognition of ICA faces.

Thermodynamics proof of sensory learning and implication of mammal homeostasis

Modularity Biometric System (MBS) is an approach to support AiTR of the cooperated and/or non-cooperated standoff
biometric in an area persistent surveillance. Advanced active and passive EOIR and RF sensor suite is not considered
here. Neither will we consider the ROC, PD vs. FAR, versus the standoff POT in this paper. Our goal is to catch the
"most wanted (MW)" two dozens, separately furthermore ad hoc woman MW class from man MW class, given their
archrivals sparse front face data basis, by means of various new instantaneous input called probing faces. We present an
advanced algorithm: mini-Max classifier, a sparse sample realization of Cramer-Rao Fisher bound of the Maximum
Likelihood classifier that minimize the dispersions among the same woman classes and maximize the separation among
different man-woman classes, based on the simple feature space of MIT Petland eigen-faces. The original aspect consists
of a modular structured design approach at the system-level with multi-level architectures, multiple computing
paradigms, and adaptable/evolvable techniques to allow for achieving a scalable structure in terms of biometric
algorithms, identification quality, sensors, database complexity, database integration, and component heterogenity. MBS
consist of a number of biometric technologies including fingerprints, vein maps, voice and face recognitions with
innovative DSP algorithm, and their hardware implementations such as using Field Programmable Gate arrays (FPGAs).
Biometric technologies and the composed modularity biometric system are significant for governmental agencies,
enterprises, banks and all other organizations to protect people or control access to critical resources.

Modular biometric system

A ceramic material cooled with liquid nitrogen can conduct electricity without resistance, i.e., a supercurrent. This supercurrent is two dimensional consisting of pairs of electron holes streaming in synch along the plane parallel to the orthorhombic crystalline minor axes composed of copper and oxygen atoms. Ceramic superconductors do not completely expel electromagnetic fields from their interiors which therefore permits radiation interactions. A super-triode designed for optical sensing has a radiation grid along the major c-axis, orthogonal to the superconducting plane where cathode and anode supercurrents crossflow each other in a highway overpass architecture. By design, the overpass anode current occludes the radiation from the underpass cathode current, with their resistance ratio producing a sensitive, single photon sensing capability. A neurocomputer designed to operate at a high speed has a double layer architecture for feedback control, similar to the adaptive resonance theory for self-clustering pattern classification. Super-triode focal plane array also have many advantages over traditional CCD arrays in the field of imaging. The point-by-point direct and dense read-out supports a wave front sampling instantaneously, which exhibits the direction finding capability, as well as the possibility of wave-front correction for sharper image formation when coupled in-situ with a neurocomputer.

http://ieeexplore.ieee.org/iel4/499/4080/00692018.pdf

High Tc Superconductor Optoelectronic Switch For High Density Sensing & Neurocomputing

. We describe an optoelectronic system to extract gray-scale texture features. These systems utilize a nonlinear resistive grid to per-form a 2-D pseudowavelet transform of the optical input image. Texturefeatures are computed using first- and second-order variance estimatesof the transform coefficients. Some preliminary results are presented thatdemonstrate the natural segmentation that the nonlinearity provides at the boundary of two dissimilar textures and the utility of the extracted features for texture discrimination. Subject terms: wavelet transforms; electronics; optics; texture; discrimination;segmentation.Optical Engineering 31(9), 1886- 1892 (September 1992). First and foremost, the texture discrimination ability of retinal-based biological systems provides a working prototype forthis approach. Second, optoanalog implementation of ourhypothetical retina offers the potential of parallel prepro-cessing. The postpnocessing is based on well-understoodparametric and nonparametric statistical techniques.5 Thispermits an analysis of the contributions of individual fea-tunes produced in the preprocessing and gives us a capabilityto follow an ''evolutionary'

o ptoelectro n i c torn p utati on of waveletli ke-based features

Conventional sub-Nyquist sampling methods for analog signals exploit prior information about the spectral sup-port. In this paper, we consider the challenging problem of sub-Nyquist sampling of bandlimited or sparse signals. Can the new paradigm Compressive Sampling (CS) challenge Shannon-Nyquist? Our preliminary development goal is to study and evaluate to reduce the system process load and still provide sufficient and useful information. We also review radio frequency process and Shannon Nyquist Sampling Theorem. 1.

Harold H. Szu

Papers

Thermodynamics proof of sensory learning and implication of mammal homeostasis

Modular biometric system

High Tc Superconductor Optoelectronic Switch For High Density Sensing & Neurocomputing

o ptoelectro n i c torn p utati on of waveletli ke-based features

Elucidating compressive sensing from Nyquist critical sampling