Dispersive and composite nanomaterials based on multi-walled and single-walled carbon nanotubes and its conjugates with dye of zinc phthalocyanine were produced. The composition and the structure of dispersive and composite materials were investigated using analytical methods of spectroscopy and microscopy. Nonlinear characteristic of nanomaterials of limiters by direct nonlinear scanning and Z-scan method were investigated. Studies suggest the possibility of using such nanomaterials in laser intensity limiters. Proposed threshold model characterizing limiters of powerful laser radiation takes into account the threshold nature of nonlinear interaction of irradiation with the nonlinear material. Threshold effect of nonlinear interaction of laser irradiation with several nonlinear material based on multi-walled and single-walled carbon nanotubes was experimentally found. It was shown that threshold model fit better with experimental data of Z-scan.
An approach for fuzzy-valued nonmonotonic logics, based on the algebra of Fourier-dual operators, to be implemented
by Fourier-holography technique is proposed. Results of computer simulation based on experimentally implemented
logics are presented.
In this paper we consider linguistic model as an algebraic model and restrict our consideration to the semantics only. The concept allows “natural-like” language to be used by human-teacher to describe for machine the way of the problem solving, which is based on human’s knowledge and experience. Such imprecision words as “big”, “very big”, “not very big”, etc can be used for human’s knowledge representation. Technically, the problem is to match metric scale, used by the technical device, with the linguistic scale, intuitively formed by the person. We develop an algebraic description of 4-f Fourier-holography setup by using triangular norms based approach. In the model we use the Fourier-duality of the t-norms and t-conorms, which is implemented by 4-f Fourier-holography setup. We demonstrate the setup is described adequately by De-Morgan’s law for involution. Fourier-duality of the t-norms and t-conorms leads to fuzzy-valued logic. We consider General Modus Ponens rule implementation to define the semantical operators, which are adequate to the setup. We consider scales, formed in both +1 and -1 orders of diffraction. We use representation of linguistic labels by fuzzy numbers to form the scale and discuss the dependence of the scale grading on the holographic recording medium operator. To implement reasoning with multi-parametric input variable we use Lorentz function to approximate linguistic labels. We use an example of medical diagnostics for experimental illustration of reasoning on the linguistic scale.
Linguistic modeling is the way, which allows human-like language to be used to teach machine. The task is to match metric scale of the machine with linguistic scale of the teacher. We discuss application of Fourier-holography technique to this task. We formulate logical description of 4-f Fourier-holography setup. Restrictions on the model, determined by property of real recording media are discussed. An example of linguistic measurement by the setup is presented.
In this paper we discuss our approach to based on holographic techniques implementation of neuro-fuzzy predictor for processes, described by Fractal Brownian Motion (FBM) model. We use the model of the predictor as a Riemann - Stieltjes integral over the observed traffic of specific weight function. We discuss two-layered bi-directional optical neural network to find our solution. To find the weight function we use non-linearity in the correlation layer of the neural network. In our experiments we used air-photograph of forest as this kind of images demonstrates self-similarity property and can be described by the FBM model. As a first step we used approximate solution for the weight function, achieved by using binary filtering function in the correlation layer. We demonstrate experimental results and discuss directions of our future investigations.
We consider algebraic foundations of geometrical optics approximation. The consideration is aimed at optical implementation of computational intelligence models. Theory of triangular norms and measure means are used to formulate the description. The process of negative photo-registration is considered as the implementation of the negation, which generates the algebra. Three approximations of negative recording media transmittance are considered: linear, involutive, and non-involutive one. Optically realizable orders and relations of fuzzy numbers, fuzzy sets and images are considered.
Optics has a number of deep analogies with main principles of Computational Intelligence. We can see strong analogies between basic optical phenomena, used in Fourier-holography, and mathematical foundations of Fuzzy Set Theory. Also, analogies between optical holography technique and principles of Neural Networks Paradigm can be seen. Progress in new holographic recording media with self-developing property leads to Evolutionary Computations holographic realization. Based on these analogies we review holographic techniques from two points of view: Fuzzy Logic and Fuzzy relations.
Our main interest is to formulate algebraic description of both Geometrical and Fourier-approximations of Optics. We use triangular- norms based approach to formulate algebraic descriptions for both geometrical and Fourier-approximations of optics. To take into consideration real nonlinearity of recording media the measure theory is used. Unlimited plane wave as an universal set is considered. For geometrical optics an algebraic model as designed. Logical operators, parameterized by recording media operators, are defined. To extend dynamical range of negative recording media from linear to over-exposure one, non-additive measure is defined. Algebraic properties of the model in dependence on the approximating function choosing are discussed. Theoretical conclusions are illustrated by experimental measuring and numerical simulation for two-layered optical system. For Fourier- approximation Fourier-duality is used to design semi-ring by DeMorgan's law using, 4-f Fourier-holography setup constructs sequence of model's elements, corresponding to Peano's axioms. Convolution is an abstract addition and correlation is an abstract subtraction in the model Fuzzy- valued measure is defined and fuzzy-value logic is designed. Theoretical conclusions are confirmed by experimental demonstration of logical inference Generalized Modus Ponens realization.
Our main interest is to establish connections between Optics and Fuzzy Set Theory. We formulate the t-norms based algebraic description of both geometrical and Fourier- approximations of optics. Geometrical optics implements probabilistic operators under the linear approximation of negative recording process. For real recording media not Zadeh's, but Sugeno negation is more appropriate approximation. It gives dual to the product t-norm family of t-conforms, parameterized by the recording medium and developing process properties. Fourier-optics allows Fourier-duality to be used in addition to N-duality. Fourier-holography setup implements semiring with product t- norm and F-dual family of t-conorms - sum-product convolutions, parameterized by holographic recording medium operator. Implication operator, implemented by Fourier- holography technique, is defined. Experimental realization of General Modus Ponenes rule by holographic fuzzy interference engine is presented.
Construction of algebra of fuzzy numbers by Fourier holography techniques is presented. Implementation of arithmetic operations on both conventional and VSOP fuzzy numbers by both with plane reference wave and joint- transform setups is discussed. Realization of both addition and subtraction operations is presented.
Hologram as a fuzzy relation of two subsets is treated. Fuzzy number as a Fourier-transform of the distribution in the plane of hologram is determined. To generate monoid of fuzzy numbers, convolution as an inner composition law is used. Realization of extended ariphmetic operations by holography is discussed.
Model of Artificial Vision is discussed. The task is to find the part of reference pattern that presents in the object image. Condition is the task has to be solved in the framework of the Classifical Approach to the image understanding, i.e. without formal description of patterns. In two-layered bidirectional optical neural network image layer as a comparison layer is realized. Function of selective attention as filtering function in the correlation layer is involved. Energy function for the NN is defined as scalar product of object image and formed by NN expectation.
The idea of the Plural Partial Associations is proposed to designate the case of associatability having the prototypes in ordinary life, but not described by the Associative Memory principle. The method based on computation of the correlation functions of the input vector with the back of the reference vectors is discussed as a one of the possible way to realize Plural Partial Associations and neural network model to implement this way is discussed. The possibility of this NN model implementation by two-layered bidirectional optical neural network used the Van der Lught correlator is discussed by the published before theoretical and experimental results.
The multiply scattered light intensity was measured when a narrow laser beam illuminated a turbid medium. The position of the pointlike effective diffusive source appeared to be unexpectedly deep. It is important in diffusing-wave spectroscopy.
A method of the numerical investigation of the energy relief of the neural networks (NN) with the correlation interconnections realized by holographic correlator is discussed. The analytical and numerical modeling of the energy relief sectioned by hypersurfaces formed by the transformations of the object image to reference is used.
Common principles of development and application of reverse electrographic and electrophotographic material with thermoplastic treatment are discussed. Possibilities of purposeful modification of these materials by intrachain doping on the stage of synthesis or by macromolecular design methods are shown.
Optical neural network formed by placing the holographic correlator into the linear resonator is discussed. Variation of the attractor position by means of inhibitory optical interconnections to achieve new solution types is proposed. The experimental results are presented.
The neural network concept of the complex system for pattern recognition on the complex background is proposed. The main components of this concept are the complex space of the features and the mode of information complexing. The concept about neurophysiological mechanisms of the vision search on the complex background is used as the neural network paradigm of multi-sensor information processing.
The adaptive neural network model for pattern classification on the complex background is proposed. The method of the detection and extraction of the unknown changing patterns, based on the optical correlation, is proposed. The optical implementation of that NN model, formed by placing the optical correlator in a linear resonator to realize the vectors comparison and image preparation, is discussed.
The possibilities of the optical neural network formed by placing the optical correlator in a linear resonator to realize the vectors comparison and image preparation are discussed. The adaptive neural network model to pattern recognize on the complex background is proposed. The optical implementation of that NN model is discussed.
The method of the numerical evaluation of the influence of the geometrical distortions on the image correlation without the limitation on the type of the distortions is discussed. The main types of the distortions are described. The results of the theoretical modeling and experiments on the holography correlator are presented.
Types of solutions are shown to which the process can converge in an optical neural network made of a Van der Lught correlator inside a linear resonator. Conditions for obtaining the desired type of solution are specified. For this architecture associative memory is a particular case of a more general form of solutions. The results of experimental testing are reported.
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