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A study reports about a three-terminal organic memory device, which is realized by wiring out the metal-nanocluster layer of the organic electrical bistable device (OBD) as the middle electrode. Details of the device mechanism are provided and the findings indicated that the device shows electrical bistability and memory effect.

We describe an active optical system that both measures and corrects the aberrations introduced when writing three-dimensional bit-oriented optical memory by a two-photon absorption process. The system uses a ferroelectric liquid-crystal spatial light modulator (FLCSLM) configured as an arbitrary wave-front generator that is reconfigurable at speeds as great as 2.5 kHz. A method of aberration measurement by the FLCSLM wave-front generator is described. The same device is also used to correct the induced aberrations by preshaping the wave fronts with the conjugate phase aberration as well as to scan the focal spot in three dimensions. Experimental results show the correction of both on- and off-axis aberrations, allowing the writing of data at depths as great as 1 mm inside a LiNb[O.sub.3] crystal. OCIS codes: 210.4680, 210.2860, 010.1080, 220.1000, 230.6120.

Research is presented concerning the investigation of the relationships which exist between the dielectric and microstructure properties of epitaxial films of ferroelectric barium titanate.

Absorption cross-sectional measurements and model predictions of 25 disks with moderate electrical conductivity were made. The disk radii span part of the resonance region, and their thicknesses are an order of magnitude less than the skin depth. A photoacoustic apparatus, with a 35-GHz microwave source, was used to measure the absorption cross sections. The disks tend to be more absorbing when they are edge-on rather than broadside to the incident microwaves. Also they absorb most efficiently near a size parameter of 1. Model predictions generally agree with the measured magnitudes and trends in the data.

We propose a multilayer associative memory with a winner-take-all operation on the inner product between an input and stored exemplars. The winner-take-all operation is performed by a unit-step operation with an adaptive-threshold strategy. We show that the multilayer-associative-memory unit-step operation with an adaptive-threshold strategy has a high noise immunity and a large storage capacity, and it is also capable of extending to a gray-level associative memory with a phase-representation technique. A hybrid optical implementation with a proof-of-concept experiment is also provided. Key words: Winner-take-all, Maxnet, misretrieval probability, storage capacity, associative memory.

A learning and recall algorithm for optical associative memory based on the conventional correlation-learning method with three effective improvements (sparse-encoding method, constant-total-activity method, and binary memory) is proposed from a viewpoint of practical implementation. It is shown that the algorithm is suitable for implementation with a bistable spatial light modulator such as a ferroelectric liquid-crystal spatial light modulator, which has high resolution and a fast response time. The results of theoretical analysis and simulations indicate that the algorithm permits an associative-memory system with a large memory capacity to be realized. An example of an optical system for executing this algorithm is proposed. To determine the performance specifications that are required for the various optical components within the system, we simulate and evaluate the effect of noise (which is caused by nonideal components) on system performance. These results show that the system is robust in the presence of predicted noise levels. Key words: Optical computing, neural network, associative memory, correlation learning, bistable spatial light modulator, sparse encoding.

We present a review of the emerging optically addressed ferroelectric memory with nondestructive readout as a nonvolatile memory technology, identify its high-impact applications, and project on some novel device designs and architectures that will enable its realization. Based on the high-speed bidirectional polarization-dependent photoresponse, simulation of a readout circuit for a 16-kbit VLSI ferromemory chip yields read-access times of [approximately] 20 ns and read-cycle times of [approximately] 30 ns ([approximately] 34 ns and [approximately] 44 ns, respectively, within a framework of a radiation-hard environment), easily surpassing those of the conventional electrical destructive readout. Extension of the simulation for a 64-kbit memory shows that the read-access and -cycle times are only marginally increased to [approximately] 21 ns and [approximately] 31 ns, respectively ([approximately] 38 ns and [approximately] 48 ns, with a radiation-hard readout circuitry). Commercial realization of the optical nondestructive readout, however, would require a reduction in the incident (optical) power by roughly an order of magnitude for the readout or an enhancement in the delivered power-to-size ratio of semiconductor lasers for compact implementation. We present a new two-capacitor memory-cell configuration that provides an enhanced bipolar optoelectronic response from the edges of the capacitor at incident power as low as [approximately] 2 mW/[[[micro]meter].sup.2]. A novel device design based on lead zirconate titanate with the c axis parallel to the substrate is suggested to reduce the requirement of incident optical power further by orders of magnitude.

We propose a novel scheme that optically implements various types of binary sequential logic elements. This is based on a polarization-encoded optical shadow-casting system. The proposed system architecture is capable of implementing synchronous as well as asynchronous sequential circuits owing to the inherent structural flexibility of optical shadow casting. By employing the proposed system, we present the design and implementation schemes of a J-K flip-flop and clocked R-S and D latches. The main feature of these flip-flops is that the propagation of the signal from the input plane to the output (i.e., processing) and from the output plane to the source plane (i.e., feedback) is all optical. Consequently the efficiency of these elements in terms of speed is increased. The only electronic part in the system is the detection of the outputs and the switching of the source plane.

Side-gated structures in a delta-doped layer facilitate the description of a single-electron memory cell. The employment of a semiclassical model is explains the characteristics of this device. The memory operates only at very low temperatures and can be made to operate at room temperatures by forming islands at a scale of less than 1 nanometer. Multiple-tunnel junction is the key component of a single-electron memory.

A perfectly convergent unipolar neural associative-memory system based on nonlinear dynamical terminal attractors is presented. With adaptive setting of the threshold values for the dynamic iteration for the unipolar binary neuron states with terminal attractors, perfect convergence is achieved. This achievement and correct retrieval are demonstrated by computer simulation. The simulations are completed (1) by exhaustive tests with all of the possible combinations of stored and test vectors in small-scale networks and (2) by Monte Carlo simulations with randomly generated stored and test vectors in large-scale networks with an M/N ratio of 4 (M is the number of stored vectors; N is the number of neurons is less than or equal to 256). An experiment with exclusive-OR logic operations with liquid-crystal-television spatial light modulators is used to show the feasibility of an optoelectronic implementation of the model. The behavior of terminal attractors in basins of energy space is illustrated by examples.

The optical disk is a computer-addressable binary storage medium with very high capacity. More than 10 to the tenth power bits of information can be recorded on a 12-cm-diameter optical disk. The natural two-dimensional format of the data recorded on an optical disk makes this medium particularly attractive for the storage of images and holograms, while parallel access provides a convenient mechanism through which such data may be retrieved. In this paper we discuss a closed-loop optical associative memory based on the optical disk. This system incorporates image correlation, using photorefractive media to compute the best association in a shift-invariant fashion. When presented with a partial or noisy version of one of the images stored on the optical disk, the optical system evolves to a stable state in which those stored images that best match the input are temporally locked in the loop.

Optical implementation of a three-dimensional associative-memory tensor with 32 X 32 X 32 weighted interconnections between elements of the input and output vectors in quadratic associative memory is obtained by the use of persistent spectral hole-burning media. The capability of the present optical scheme for correcting errors in the input image is demonstrated.

A compression - attraction-sphere associative-memory model is proposed. An optoelectronic implementation of its inner-product architecture using an optical spatial pattern-encoding method is demonstrated by computer simulations and preliminary experiments.

An architecture for a novel adaptive optical processing system using optical associative memory with learning capability is proposed. The optical system consists of an optical preprocessor for feature extraction and optical associative memory. The feature-extraction ability can give excellent processing capability to the optical associative memory. In order to demonstrate this system, an optical Fourier transform is used as the preprocessor, and the system can achieve shift invariance. An all-optical configuration of the system is proposed, and the experimental results applied to handwritten-character recognition by using an hybrid opto-electronic system are shown and discussed.

The content-addressable network (CAN) is an efficient, intrinsically discrete training algorithm for binary-valued classification networks. The binary nature of the CAN network permits accelerated learning and significantly reduced hardware-implementation requirements. A multilayer optoelectronic CAN network employing matrix-vector multiplication was constructed. The network learned and correctly classified trained patterns, gaining a measure of fault tolerance by learning associative solutions to optical hardware imperfections. Operation of this system is possible owing to the reduced hardware accuracy requirements of the CAN learning algorithm.

A gray-level discrete associative-memory neural network based on object decomposition and composition is presented. By decomposing a gray-level pattern into bipolar/binary subpatterns, a gray-level discrete associative memory can be constructed from the composition of the subpattern channel results. Preprocessing for removing dc bias and normalizing the gray-level scale is performed on the input gray-level pattern. This eliminates the mismatching and saturation problems caused by bias level, which shifts the pattern gray levels throughout the pattern. Computer-simulation and optical-experimental results for a gray-level interpattern association model are shown to be consistent with the theoretical model.

The design, analysis, and feasibility of a novel motionless-head parallel readout optical-disk system are presented. The system is designed to read data blocks distributed radially on the disk's active surface, and it has the unique advantage that no mechanical motion of the head is required for fast access, focusing, or tracking. Data access is achieved solely through the disk rotation, and the entire memory can be read in one rotation. In principle, this permits a data rate of up to 1 Gbyte/s. The data blocks are one-dimensional Fourier-transform computer-generated holograms, each reconstructing one column of a two-dimensional output image. Owing to the information redundancy and shift invariance properties of Fourier-transform holograms, tracking and focusing servo requirements are eliminated. A holographic encoding method is developed to produce high signal-to-noise ratio reconstructions and to reduce significantly the radial alignment requirements of the recorded data bits. The optical readout system consists of only three cylindrical lenses. Two of these may be replaced by a single hybrid diffractive -refractive optical element for easier system alignment and better optical performance, i.e., reduced aberrations and improved resolution. The throughputs and retrieval times of this parallel readout optical-disk system make it well suited to a variety of parallel computing architectures, including a high-performance optoelectronic associative memory (Proc. Soc. Photo-Opt. Instrum. Eng. 1347, 86 (1990)).

A method to achieve bipolar performance in a single-channel optical associative memory is presented. By coding the biased interconnection weights, a distributed background, and an input-dependent dynamic threshold on a single mask, we construct an optical network with both bipolar neural states and bipolar interconnections. Content addressability and other properties are improved by the introduction of a distributed background, as compared with the case in which this background is not used. Computer simulations and optical experiments are performed based on the Hopfield algorithm. Key words: Bipolar neural states, neural networks, optical implementation of neural networks.

For the purpose of reducing the spurious states in a Hopfield neural net for associative memory, we invoke terminal attractors. In achieving the optical implementation of the terminal-attractor-based associative memory (TABAM) as described in this paper, we first prove the existence of the terminal-attractor model with binary neuron representation. We then present several one- and two-dimensional optical architectures for the TABAM. Finally, as an example, we experimentally demonstrate an inner-product optical neural model using liquid-crystal spatial light modulators with engineering approximations and discuss how to apply the inner-product model to build a two-dimensional parallel processing TABAM. Key Words: Terminal attractor, associative memory, Hopfield model, inner-product architecture, liquid-crystal spatial light modulators.

A new associative memory system applying incoherent correlators is presented. With this system, which is composed of a nonlinear processor and optical-electronic feedback loop, memorized patterns can be recalled without cross talk. To realize a high association ability and stable operation, a synthetic discriminant function filter is applied. Results of the computer simulation and actual experiments by using the system that is constructed here are demonstrated. Key words: Optical information processing, associative memories, synthetic discriminant functions, incoherent optical correlator.

The construction and operation of a 50-MHz 64 x 16 bit fiber-optic bit-serial delay-line memory is described. It consists of [LinbO.sub.3] directional coupler switches, fused-fiber couplers, and a 4.17-km fiber loop. It is a subsystem of a bit-serial optical computer under construction by our group. We discuss delay and clock source stability requirements for the long delay line in the face of a limited phase error tolerance. The reliability testing of the memory subsystem is described. The degradation of data in the memory loop as the phase error tolerance is exceeded by a small amount is studied through the temperature dependence of the memory loop. Data are presented for the memory-loop stability with respect to temperature variations. The memory subsystem design and construction is presented. The results of these experiments support the feasibility of a 100-MHz 128 x 16 bit memory.

Associative processing based on content-addressable memories has been argued to be the natural solution for nonnumerical information processing applications. Unfortunately, the implementation requirements of these architectures when one uses conventional electronic technology have been cost prohibitive; therefore associative processors have not been realized. Instead, software methods that emulate the behavior of associative processing have been promoted and mapped onto conventional location-addressable systems. However, this does not bring about the natural parallelism of associative processing, namely, the ability to access many data words simultaneously. Optics has the advantage over electronics of directly supporting associative processing by providing economic and efficient interconnects, massive parallelism, and high-speed processing. The principles of designing an optical content-addressable parallel processor (OCAPP) for the efficient support of parallel symbolic computing are presented. The architecture is designed to exploit optics advantages fully in interconnects and high-speed operations. Several parallel search-and-retrieval algorithms are mapped onto an OCAPP to illustrate its capability of supporting parallel symbolic computing. A theoretical performance analysis of these algorithms is presented. This analysis reveals that the execution times of the parallel algorithms presented are independent of the problem size, which makes the OCAPP suitable for applications in which the number of data sets to be operated on is high (e.g., massive parallel processing). A preliminary optical implementation of the architecture with currently available optical components is also presented.

An associative memory is implemented by using a binary phase-only filter as the memory element in a two-focal-length (2-f) correlator architecture. A sharp autocorrelation peak, combined with the 2-f architecture, allows the noise to be separated adequately from the signal such that a simple plane mirror can be used in the correlation plane instead of a nonlinearity. Key words: Associative memory, binary phase-only filter, optical correlator.

We have developed a new holographic associative memory based on adaptive learning, which uses a learning pattern method (LPM). This LPM utilizes the simple optical implementation of outer-product learning. However, we have obtained a better performance from adaptive learning. Results from the optical experiment and computer simulation are represented. Key words: Holographic associative memory, neural networks, pattern recognition.

A detailed study on the effect of different thicknesses of Hf[O.sub.2] high-k interfacial layer between double-stacked layers of Ag nanocrystals formed by a chemical synthesis and thermal decomposition method is presented. For this study transmission electron microscopy and x-ray diffraction analysis are used.

The spatial distribution of two-photon excitation created by crossed focused Gaussian beams is shown. The effective volume calculation for the two-photon interaction of crossed Gaussian beams is presented. The dimensions of cubic and parallelepiped volumes, in which half of the two-photon interaction is localized, are determined. The memory densities of two-photon three-dimensional memory for crossed focused beams and one focused beam are compared. OCIS codes: 110.2970, 190.4180, 210.4680, 220.2560.

We experimentally demonstrate and characterize a memory module that features selective page erasure and readout persistence using the localized recording method in doubly doped LiNb[O.sub.3]. Pages of information can be selectively erased without partially erasing the whole memory. Data pages can be written over erased pages multiple times. Information is read millions of times before refreshing is required. We quantify the optical quality of the holograms by measuring their signal-to-noise ratio for a memory size up to 100 holograms. A compact phase-conjugate readout architecture is also presented and experimentally demonstrated. OCIS codes: 210.0210, 210.2860.

We propose and demonstrate a fractional Fourier domain encrypted holographic memory using an anamorphic optical system. The encryption is done by use of two statistically independent random-phase codes in the fractional Fourier domain. If the two random-phase codes are statistically independent white sequences, the encrypted data are stationary white noise. We exploit the capability of an optical system to process information in two dimensions by using two different sets of parameters along the two orthogonal axes to encode the data. The fractional Fourier transform parameters along with the random-phase codes constitute the key to the encrypted data. The knowledge of the key is essential to the successful decryption of data. The decoding of the encoded data is done by use of phase conjugation. We present a few experimental results. [C] 2001 Optical Society of America OCIS codes: 210.2860, 070.5040.