Optical implementations of radial basis classifiers

We describe two optical systems based on the radial basis function approach to pattern classification. An optical-disk-based system for handwritten character recognition is demonstrated. The optical system computes the Euclidean distance between an unknown input and 650 stored patterns at a demonstrated rate of 26,000 pattern comparisons/s. The ultimate performance of this system is limited by optical-disk resolution to 10^11 binary operations/s. An adaptive system is also presented that facilitates on-line learning and provides additional robustness

Optical memory: introduction by the feature editors

The contributions to this feature issue represent a wide range of topics in optical memory

Programmable image associative memory using an optical disk and a photorefractive crystal

The optical disk is a computer-addressable binary storage medium with very high capacity. More than 10^10 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

Image correlators using optical memory disks

Image correlators are described and experimentally demonstrated that are implemented using optical memory disks to store a large library of reference images

Optical memory disks in optical information processing

We describe the use of optical memory disks as elements in optical information processing architectures. The optical disk is an optical memory devicew ith a storage capacity approaching 1010b its which is naturally suited to parallel access. We discuss optical disk characteristics which are important in optical computing systems such as contrast, diffraction efficiency, and phase uniformity. We describe techniques for holographic storage on optical disks and present reconstructions of several types of computer-generated holograms. Various optical information processing architectures are described for applications such as database retrieval, neural network implementation, and image correlation. Selected systems are experimentally demonstrated

Block-wise motion detection using compressive imaging system

A block-wise motion detection strategy based on compressive imaging, also referred to as feature-specific imaging (FSI), is described in this work. A mixture of Gaussian distributions is used to model the background in a scene. Motion is detected in individual object blocks using feature measurements. Gabor, Hadamard binary and random binary features are studied. Performance of motion detection methods using pixel-wise measurements is analyzed and serves as a baseline for comparison with motion detection techniques based on compressive imaging. ROC (Receiver Operation Characteristic) curves and AUC (Area Under Curve) metrics are used to quantify the algorithm performance. Because a FSI system yields a larger measurement SNR (Signal-to-Noise Ratio) than a traditional system, motion detection methods based on the FSI system have better performance. We show that motion detection algorithms using Hadamard and random binary features in a FSI system yields AUC values of 0.978 and 0.969 respectively. The pixel-based methods are only able to achieve a lower AUC value of 0.627. © 2010 Elsevier B.V. All rights reserved.postprin

Object reconstruction from adaptive compressive measurements in feature-specific imaging

Static feature-specific imaging (SFSI), where the measurement basis remains fixed/static during the data measurement process, has been shown to be superior to conventional imaging for reconstruction tasks. Here, we describe an adaptive approach that utilizes past measurements to inform the choice of measurement basis for future measurements in an FSI system, with the goal of maximizing the reconstruction fidelity while employing the fewest measurements. An algorithm to implement this adaptive approach is developed for FSI systems, and the resulting systems are referred to as adaptive FSI (AFSI) systems. A simulation study is used to analyze the performance of the AFSI system for two choices of measurement basis: principal component (PC) and Hadamard. Here, the root mean squared error (RMSE) metric is employed to quantify the reconstruction fidelity. We observe that an AFSI system achieves as much as 30% lower RMSE compared to an SFSI system. The performance improvement of the AFSI systems is verified using an experimental setup employed using a digital micromirror device (DMD) array.published_or_final_versio

On the Contribution of Higher Azimuthal Modes to the Near- and Far-Field of Jet Mixing Noise

The prediction of jet mixing noise is studied using a stochastic realization of the Tam & Auriault source model. The acoustical sources are generated by means of the Random Particle-Mesh Method (RPM), which utilizes turbulence statistics as provided by solu- tions to the Reynolds Averaged Navier-Stokes (RANS) equations. The generated stochas- tic sound sources closely realize the two-point cross-correlation function used in the jet noise model to prescribe the fine-scale sound source. The RPM code is coupled with the DLR CAA solver PIANO. The azimuthal-modal decomposed linearized Euler equations are applied as governing equations. With this approach, it is possible to evaluate jet noise spectra at any position in the near-field. Based on an azimuthal decomposition, 3-D sound radiation from the jet can be reproduced at the computational price of a few axisymmetric 2-D computations. Furthermore, it will be shown, that we are able to verify the imple- mented methodology with the results published for the genuine model. The spectra are correctly predicted in terms of sound pressure levels, Mach scaling exponent and spectral shape. A Strouhal number range of up to St = 10 can be covered using the first six az- imuthal mode components of the broadband source. To reach higher Strouhal numbers more azimuthal modes have to be adopted. The presented results reveal the importance of individual azimuthal contributions to the total spectra. To evaluate the spectra in the far-field, the generated near-field noise is extrapolated with a modal Ffowcs-Williams & Hawkings (FWH) method. For the static single stream jet (Ma = 0.9) two different kinds of extrapolation were used - a simplified extrapolation and the modal FWH method. With this computational case, it was possible to predict a jet noise spectrum in the range of St = 0.01 . . . 20. To investigate the effect of different nozzle configurations on sound gener- ation, different nozzle configurations, i.e. dual-stream nozzles with and without nozzle lip treatments are simulated. Good agreement with experimental data for the noise reduction potential of nozzle lip treatments is found