Electro-optical Implementation Research Articles

Non-spectroscopic sensing enabled by an electro-optical reservoir computer

A fully bio-inspired apparatus to perform non-spectroscopic sensing to discriminate and determine the constituent concentrations of a chemical mixture is proposed. Here, fully bio-inspired means that it is comprised of a biomimetic sensor and a neuromorphic signal processor. The sensor is similar to the human eye in terms of its trichromat architecture and overlapping spectral response. The information processor is a neuromorphic system based on an electro-optical implementation of a reservoir computer. A time-stepping signal algorithm based on the Z -bilinear transformation has been developed to realistically simulate the electro-optical reservoir computer; this demonstrates the discrimination and chemical concentration determination tasks. We believe such an apparatus offers potential benefits in areas in which chemical composition needs to be monitored in real time, for example in chemical processing, and food-beverage (fermentation/brewing) and environmental monitoring.

Electrooptical Comparator: From Formula to Implementation

This paper is concerned with a process of transforming the mathematical representation of a multithreshold comparator to electrooptical implementations. The basic comparator converts an analog input into one of two levels at its (binary) output. If this functionality can be made periodic (as a function of the analog input), efficient implementation of analog-to-digital conversion can be realized. This paper begins by modeling such functionality as a square-wave via its representation as a Fourier series. Some mathematical manipulations are then performed aimed at tailoring the obtained representation for implementation by optical components such as waveguides and microring resonators. Thus, three basic integrated-optical devices are proposed for realizing a comparator with well-defined binary output levels and a steep transition slope between these levels.

All-Optical Stochastic Logic Gate Based on a VCSEL With Tunable Optical Injection

We study the dynamics of a vertical-cavity surface-emitting laser with continuous-wave orthogonal optical injection from a tunable laser. We use the dynamical properties of polarization bistability and the interplay with internal or external noise to demonstrate numerically a reliable logic output to two logic inputs encoded in the optical frequency of the injected light. This all-optical configuration is more than ten times faster than the electro-optical implementation and has the advantage of operating at constant injection power.

Ultrafast Electrical Signal Electro-Optic Sampling Test Theory and Test System

Discussed the principle of electro-optic sampling technique and implementation methods of Ultra-fast electrical signals, the electric field of electro-optical crystal and sampling pulses as well as the interaction between the principle of time scanning unit, established the coplanar waveguide parameters model, and analyzed the technical indicators of test system.

Securing color image using discrete cosine transform in gyrator transform domain structured-phase encoding

A new method for securing color image using discrete cosine transform in gyrator transform domain structured-phase encoding is proposed. In this proposal, the structured phase mask is a zone plate phase function. The input color image to be encrypted is decomposed into three channels: red, green, and blue. Each of these channels is encrypted independently by changing its spatial distribution of pixel value by discrete cosine transform, and encoded with structured phase mask. The gyrator transform is performed on resultant spectrum. Structured phase mask, discrete cosine transform, and gyrator transform are employed twice in this proposed method. The construction parameters of structured phase mask and angle parameters of gyrator transform in each channel are principal encryption keys. The schematic electro-optical implementation has been presented. The proposed architecture does not require axial movements. The effectiveness of the proposed algorithm is demonstrated against the chosen and known plaintext attacks. Numerical simulations are made to verify the security, validity, and capability of the proposed method.

Noise Properties of Harmonically Injection-Locked Oscillators

We analyze the noise properties of an injection-locked pair of oscillators whose frequencies are a harmonic of each other. This harmonic injection locking process is indirect and mediated by a nonlinear mixing process. The mixing signals are inherently correlated and, therefore, the phase noise of the locked system is lower than that of either original oscillator. We present a highly accurate time domain numerical model whose results are confirmed by an electrooptic experimental implementation.

Three-dimensional electro-optical correlation

Electro-optical implementation of a three-dimensional (3-D) spatial correlation is proposed. A 3-D scene of objects, seen from the paraxial zone, is correlated with a reference object. As an example of application, we describe a 3-D joint transform correlator that is capable of recognizing targets in the 3-D space.

A proposed electro-optical implementation of lateral inhibition with phase-only filters

This article describes a proposed electro-optical implementation of the lateral inhibition function and its simulation. Lateral inhibition is the most important adaptation property in sensory systems and with this mechanism, weak inputs to neurons are suppressed (inhibited) by strong inputs to neighboring neurons. The purpose of lateral inhibition is to enhance and emphasize boundaries. Two types of lateral inhibition filters were studied, both symmetric and antisymmetric. The antisymmetric are direction dependent and thus, four different directions were chosen. Since the electro-optic implementation relies on filtering input images in the Fourier plane, the inhibition filters used in the simulation are phase-only. The simulation takes into consideration performance of specific optical hardware components and was tested on signals that have very sharp directional edges in addition to a facial image with many contour line edges. © 1997 John Wiley & Sons, Inc. Microwave Opt Technol Lett 15: 98–102, 1997.

Optical adaptive neural networks with a ground glass for global random interconnections and local gain controls

TAG (training by adaptive gain) is a new adaptive neural network model for large-scale optical implementations. For single-layer neural networks withN input andM output neurons, the TAG model contains two different types of interconnections, i.e.MN global fixed interconnections and (N+M) adaptive gain controls. The training algorithm is based on gradient descent and error back-propagation, and is easily extensible to multilayer and/or higher-order architectures. For large-scale electrooptic implementation, the fixed global interconnections may be implemented by multifacet hologram, volume hologram or ground glass, and the adaptive gains by spatial light modulators (SLMs). The ground glass is more advantageous for random interconnections, with much higher diffraction efficiency and interconnection density. Both feed-forward signal and error back-propagation paths are implemented by a single ground glass, and adaptive learning has been demonstrated for heteroassociative memory and classifier.

Collective genetic algorithm for optimization and its electro-optic implementation

The collective genetic algorithm introduced here uses a weighted averaging process for each generation that enhances its convergence. Based on vector-matrix multiplication, this algorithm is well suited for implementation on hybrid electro-optical systems. The efficiency of the procedure is demonstrated by several laboratory experiments in which various functions were optimized.

TAG: A Neural Network Model for Large-Scale Optical Implementation

TAG (Training by Adaptive Gain) is a new adaptive learning algorithm developed for optical implementation of large-scale artificial neural networks. For fully interconnected single-layer neural networks with N input and M output neurons TAG contains two different types of interconnections, i.e., M N global fixed interconnections and N + M adaptive gain controls. For two-dimensional input patterns the former may be achieved by multifacet holograms, and the latter by spatial light modulators (SLMs). For the same number of input and output neurons TAG requires much less adaptive elements, and provides a possibility for large-scale optical implementation at some sacrifice in performance as compared to the perceptron. The training algorithm is based on gradient descent and error backpropagation, and is easily extensible to multilayer architecture. Computer simulation demonstrates reasonable performance of TAG compared to perceptron performance. An electrooptical implementation of TAG is also proposed.

Optical implementations of the alternating projection neural network

The results of two electro-optical implementations of the alternating projection neural network (APNN) are presented. Both configurations use optical matrix-vector multipliers with electronic feedback, but different spatial light modulators are employed. The first implementation is passive, employing a photographic transparency that intensity-modulates the incident incoherent light. In the second implementation, two spatial light modulators actively modulate the light, permitting real-time updating of the interconnection matrix elements. To the authors' knowledge, the implementations described are the first of the APNN.

Optical Representations For Symbolic Logic

Artificial intelligence problems are solved on electronic computers by techniques that make heavy use of address calculation and dynamic management of data storage space. Optical computing, on the other hand, is normally associated with numerical problems in which the size of the data space is fixed and addressing may be handled in a predictable manner not affected by actual data values. In this paper we categorize expert system problems by the amount of dynamic storage management required and discuss several methods for eliminating unnecessary address manipulation by careful choice of data representation. Major emphasis is placed on the implementation of the mathematical technique of resolution. Various resolution strategies are analyzed, and the effect of these strategies on storage management is assessed with a view to minimizing the complexity of processing. Finally, electro-optical implementations are considered for the major functional elements of an optical resolution system.