This PDF file contains the editorial “Editorial: The Kingslake Medal and Prize” for OE Vol. 35 Issue 08

This PDF file contains the editorial “Guest Editorial: Special Section on Applications of Neural Networks in Optics” for OE Vol. 35 Issue 07

One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with onedimensional electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high-resolution volume holographic materials and is capable of performing massive 3-D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation-shift-scaleinvariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

A hybrid neuroprocessor (NP) with bipolar optical interconnections and a personal computer (PC) for subtraction, nonlinear operation, and system control is described. The interconnection topology of the 1024 neurons in the processor can constitute either a single-layer feedback network or a multilayered feedforward one. By using different optical interconnection weight masks and corresponding PC programs, a variety of processing tasks can be performed in the NP.

A 2-D neural network and its optical implementation are presented. The neural network consists of two interconnection layers. The first layer is a modified Hamming net layer that calculates the Hamming distance between the input and each of the stored patterns. Instead of performing a winner-take-all operation, thresholding is performed within each hidden neuron. The second layer is a mapping network for pattern association. The presented neural network has fewer interconnections and a higher storage capacity than a fully interconnected Hopfield network. In comparison with multilayer perceptrons, it has advantages such as easy and direct training and unipolar binary interconnection weights and therefore is more suitable for optical implementation with currently available optoelectronic devices. The neural network can be easily reconfigured when the training set needs to be updated or extra training patterns need to be added into the training set. The attraction basins of stored patterns can be adjusted, and the input fault tolerance can be enhanced locally. An optical system employing Dammann gratings has been used in the preliminary experiments. Experimental results verified the feasibility of the neural network model as well as its optical implementation.

The neural network system with terminal attractors is proposed for pattern recognition. By the introduction of the terminal attractors, the spurious states of the energy function in the Hopfield neural networks can be avoided and a unique solution with global minimum is obtained. The computer simulations show the usefulness of the method for pattern recognition. Based on the terminal attractor neural network, we proposed the optical neural network with the terminal attractor model. The results show that the recognition rate is considerably enhanced by the introduction of the terminal attractors.

We demonstrate a new method to implement holographic associative memory based on a coherently induced double phase conjugate mirror that has phase-conjugate reflectivity larger than unity for weak reference signal over a large range of pumping-reference intensity ratio. The phase conjugator, operated with a copper-doped KNSBN crystal, serves as a novel nonlinear feedback and gain element for the associative memory system. A vanadium-doped KNSBN crystal as storage medium improves the response speed of the holographic recording process. A stored image has been completely retrieved when a partial input addresses the associative memory system.

Biological findings in the visual cortex of some small mammals are combined with the increasing evidence of feedback from the brain to the sensors to create a feedback pulse-coupled neural network. The main advantage of this algorithm is that it extracts portions of the input information with each iteration. The input is eventually altered to a steady-state output. However, during transition the input at different iterations presents primitive information of the input.

A JTC-based nearest neighbor classifier (JTC-NNC) is presented, by which shift-invariant pattern classification can be obtained. To efficiently utilize the spatial domain input plane, a non-zero-order JTC is introduced to remove the autocorrelation power spectra. In addition, a phase-transform technique is introduced into the JTC-NNC to improve the light efficiency and pattern discriminability. Finally, application of the JTC-NNC to optical character recognition is discussed, and computer simulation is provided to show the feasibility of the JTC-NNC.

Image preprocessing aimed at recognizing pattern fragments is considered. Problems of constructing homogeneous neural networks capable of selecting simple features of contour figures are studied. The filtration and selection of pattern fragments, such as line intersections, line ends, fractures, etc., are shown to be effectively accomplished by optical means.

Photorefractive waveguides that are optically modifiable can be used as the adaptive interconnection channels for optical neural networks. We investigate experimentally a refined fabrication method for the photorefractive waveguides in a lithium niobate crystal. The experimental results show that nonuniform illumination by a discontinuous movement of the focus can fabricate a better optical waveguide than uniform illumination by a continuous one. The discontinuous movement of the focus reduces the spatial overlap between the successive exposures, and avoids the redistribution of the space-charge density formed previously. This refinement results in a narrower and clearer index distribution of the waveguide. We further show that good waveguides are fabricated if the focus is scanned in a particular scanning direction that makes a small angle with the plane perpendicular to the c axis of the crystal.

We demonstrate experimentally the application of adaptive resonance theory (ART2) to disease identification from mammographic images, and the application of Kohonen’s self-organizing map and multilayer perceptron to textile defect detection using an inexpensive personal computer.

A novel fuzzy neural network (FNN) model for invariant pattern recognition is presented that combines fuzzy set reasoning and artificial neural network techniques. The presented FNN consists of three blocks: fuzzifier, fuzzy perceptron, and defuzzifier. It fuzzifies the input patterns and trains the interconnection weights according to membership functions instead of traditional binary values. The proposed FNN has been applied to 2-D binary-image pattern recognition under shift and some other types of distortions. In comparison with the classical multilayer perceptron, the FNN possesses a higher recognition rate and is more robust to input distortions.

Neural networks are employed to process signals from fiber optic sensing arrays embedded in physical structures to monitor structure parameters and to estimate structural damage in real time. The backpropagation neural network, the Kohonen neural network, and its variants the LVQ1 to LVQ5 algorithms (learning-vector quantization) are discussed in detail. Simulation experiments have been done to test the suitability of neural networks for signal processing of fiber optic sensing arrays. The results of these experiments are also given.

Mathematical morphology with gray scale structuring elements has attracted much attention, since combinations of the operations in this class can realize almost all noise-removing filters. However, the optimization method for the combination is still uncertain. In this paper, an optimization method for a mathematical morphological filter with gray scale structuring elements is proposed. This method is based on the concept of a neural network with morphological operations and on learning using simulated annealing. The method is also applied to gray scale bipolar morphological filters for image differentiation.

Recently, several image compression techniques based on neural network algorithms have been developed. In this paper, we propose a new method for image compression—the modified counterpropagation neural network algorithm, which is a combination of the selforganizing map of Kohonen and the outstar structure of Grossberg. This algorithm has been successfully used in many applications. The modification presented has also demonstrated an interesting performance in comparison with the standard techniques. It was found that at the learning stage we can use any image for a network training (without a significant influence on the net operation) and the compression ratio and quality depend on the size of the basic element (the number of pixels in the cluster) and the amount of error tolerated when processing.

The use of a simulated annealing algorithm to design quantized composite reference function (QCRF) filters is presented. Since the QCRF filters are spatial domain filters using finite quantization levels, they can be implemented at the output spatial light modulator of a joint transform correlator. The performance of the QCRF filters has been tested, in which we have shown that the detectability, accuracy, discriminability, and reliability improve as the quantization of the filter increases.

A 1-in.-diam polished diamond disk was bonded to a disk of zinc sulfide (ZnS) using a high-temperature thermoplastic adhesive to form an optical structure that may be used for infrared applications. A postbonding thermal-stress-induced deformation in the structure at room temperature was observed to decrease exponentially over time. This curvature decrease may be attributed to viscoelastic stress relaxation within the adhesive layer. The relaxation behavior of the adhesive layer was characterized over a range of temperatures above room temperature by observing curvature changes in the structure heated to these temperatures. This characterization has led to knowledge of the deformational behavior of this structure during manufacturing and service conditions. In addition, relaxation and approximate physical properties of the adhesive were extracted from the observed behavior.

Linearly polarized light backscattered from weakly scattering slabs in the cross-polarized channel manifests a symmetrical pattern. The origin and the properties of the pattern are explained and how it can be used to extract the average pathlength of the photons in the medium is shown. It is also shown that the concentration of scatterers rather than the optical depth of the sample determines the properties of the crosspolarized backscattered light.

The use of a focused Gaussian beam in the space variant micro-optical interconnection system is proposed for decreasing the alignment accuracy requirement. The relationship between both longitudinal and lateral misalignment of the light source and the power loss due to beam shift and beam spot size mismatch at the collimating lens and the photodetector are derived theoretically using ABCD matrices, and numerical simulation results are also given. A focused Gaussian microoptical system is introduced by changing the beam radius ratio on the two lenses of the one-to-one Gaussian micro-optical system from unity. It is shown that the focused Gaussian micro-optical system with a smaller beam radius on the second collimating lens than on the first one has improved misalignment tolerances compared with the one-to-one Gaussian micro-optical system.

A generalized approach is described for tailoring the dispersion characteristics of single-mode optical fibers with index distribution of nonuniform (or segmented) core and cladding profiles. This is followed by an identification of the sensitivities of the zero dispersion wavelength for various dopant level in the fiber regions. A design strategy is given as is its implementation for designing dispersion-modified optical fibers. Parameters critically affecting the dispersion-flattened or compensated single-mode fibers are outlined, together with a set of design rules.

A systematic theoretical analysis of the effect of imperfect fiber endface cleaves on the performance of extrinsic Fabry-Perot interferometric (EFPI) optical fiber sensors is presented. This analysis allows the prediction of the dynamic range of a sensor with greater confidence, and gives the tolerances of the mechanical instrument required to prepare the fiber endfaces. Good correlation with preliminary experimental results is also shown.

We propose an efficient classified vector quantizer (CVQ) technique employing the linear phase paraunitary (LPPU) M-band filter bank. Based on the asymptotic distortion of VQ, a coding gain, which includes the gain by the correlation in the vector as well as the energy compaction, is first derived. Then we design the LPPU four-band and eight-band filter banks, with various lengths, that maximize the coding gain. Among the designed LPPU filter banks, we select the LPPU fourband filter bank for the proposed CVQ technique, since we can significantly alleviate the complexity of CVQ and classify the input image more accurately with 4 X 4 blocks than with 838 blocks. However, the side information for the 4 X 4 blocks is four times that for the 8 X 8 blocks. In order to reduce the side information, we propose the quadtree method, which reduces the side information by about 50%. Simulation results demonstrate that the proposed technique yields about 0.8- to 1.0-dB peak-SNR gain over that of the Joint Photographic Experts Group in the range of 0.3 to 0.4 bits per pixel.

Partitioning of Hopfield networks into submodules is important in large-scale problems for ease of implementation, say, with optical systems having limited space-bandwidth product. Two types of decomposition and their application to image restoration are discussed. In the case of two-stage partitioning, the system functions as a pair of Hopfield subnetworks that iteratively force the energy function to a minimum. The least-squares solution is attained by iteratively switching between the two networks until convergence. The algorithms are valid for any number of partitions. Partitioning also helps avoid the problem of possible limit cycles when threshold nonlinearities are used, and the problem of nonzero diagonal elements in the interconnection matrix when the partitions are implemented in parallel.

A study was conducted to test the efficacy of detecting particulate contaminants in processed meat samples by visual observation of line-scanned x-ray images. Six hundred field-collected processedproduct samples were scanned at 230 cm2/s using 0.5 X 0.5-mm resolution and 50 kV, 13 mA excitation. The x-ray images were image corrected, digitally stored, and inspected off-line, using interactive image enhancement. Forty percent of the samples were spiked with added contaminants to establish the visual recognition of contaminants as a function of sample thickness (1 to 10 cm), texture of the x-ray image (smooth/ textured), spike composition (wood/bone/glass), size (0.1 to 0.4 cm), and shape (splinter/round). The results were analyzed using a maximum likelihood logistic regression method. In packages less than 6 cm thick, 0.2-cm-thick bone chips were easily recognized, 0.1-cm glass splinters were recognized with some difficulty, while 0.4-cm-thick wood was generally missed. Operational feasibility in a time-constrained setting was confirmed. One half percent of the samples arriving from the field contained bone slivers >1 cm long, 1/2% contained metallic material, while 4% contained particulates exceeding 0.3 cm in size. All of the latter appeared to be bone fragments.

We consider the reconstruction of a complex-valued object that is illuminated with random light (a sequence of speckle distributions) and viewed through a random phase screen. The reconstruction involves a phase retrieval based on the measurement of a series of two shortexposure Fourier intensities: the intensity of the Fourier transform of the image and the intensity of the Fourier transform of the image after transmission through an exponential filter. The method of reconstructing the object consists of the two steps: the reconstruction of the object intensity distribution from the average correlation functions of the short-exposure Fourier intensities of the unfiltered and filtered image fields and the retrieval of the object phase from object intensity distributions reconstructed from the series of the two short-exposure Fourier intensities multiplied by exponential functions. Computer-simulated examples of the reconstruction of 1-D complex objects demonstrate that the reconstruction is robust.

Some operators from the theory of texture image analysis are used to obtain a new method for the evaluation of anisotropy in planar stochastic structures. A local gradient function provides information on local anisotropy and its variability, from 2-D density images for foil materials like polymer sheets, nonwoven textiles and paper. Such images can be captured by radiography or light transmission; results are reported for a range of paper structures. The method has potential for on-line application to monitoring and control of anisotropy and its variability, as well as local density itself, in continuous manufacturing processes.

The detailed calculation of the design and working parameters of the Wollaston prisms of a Nomarski polarized interferometer using an ultrashort light pulse as a coherent source is presented. The properties of the interferometer when the prisms are in different places in the light path are also presented

A tunable IR filter capable of scanning from 8.2 to 12.8 µm has been designed, constructed, and tested. It is a first-order Fabry- Pe´ rot interferometer with piezoelectrically driven cavity spacing. Multilayer dielectric coatings for the partially transmitting mirrors were designed to minimize the wavelength-dependent phase change produced by reflection. The transmission bandwidth ranged from 2.8 to 4.0% across the tuning range. Continuous scanning at 20 Hz rates was demonstrated.

We present results on a technique for characterizing a Gires- Tournois interferometer (GTI) using a lightwave component analyzer. This apparatus measures the transfer function of the GTI in the frequency domain. By measuring this transfer function for different wavelengths of a tunable laser, we find the parameters of the GTI. These parameters are the mirror reflectivities of the GTI and the distance between the mirrors. With these parameters, it is then possible to determine the dispersion of the GTI. With this technique, we have been able to caracterize GTIs with FSR of 16.5 and 60 GHz.

An algorithm of phase-shifted image matching for the measurement of displacement from interferometric images is presented. The algorithm is capable of detecting the displacements between the interferograms captured by a CCD camera with subpixel accuracy. The phase curves are obtained from mean-square-difference calculations of any two fringe patterns shifted pixel by pixel, and the phase differences between the interferograms are computed by interpolation. An example of measurement of electrostatic force displacement by a fiber optic interferometer system is described. The experiment shows that the algorithm has the advantages of high measurement precision and high resistance to noise. The high resistance to noise of the algorithm makes it suitable for measurement even in harsh environmental conditions.

A complete system for the measurement of 3D shape and deformation of curved surface under 3D loading has been developed based on a digital speckle pattern interferometer (DSPI) and the phase shifting technique. A system incorporating an optical arrangement of four beams and a personal computer-based image processor has been devised and built. When the four beams are appropriately arranged, six sensitivity vectors are provided, of which three are independent. Measurements along these three independent vectors are jointly utilized to solve for the 3D displacement components. During the calculation of the displacements, the surface shape coordinates are required, which in our case are provided by a shape measuring procedure. This procedure is implemented by traversing one of two selected beams in the optical setup. A four-step phase retrieving algorithm is employed to automatically perform the data reduction. To this end, 16 speckle patterns are first acquired and then analyzed to obtain the surface height distribution and the 3D displacements and their derivatives. Measurement results for a closed cylindrical specimen under internal pressure are presented.

Interferometer fringe-pattern analysis using the fast Fourier transform (FFT) technology is a very precise measuring method. However, this method has not received significant attention in industry, as a result of the long calculation time for an operation, because the method processes an image using sophisticated algorithms. In this work, in order to reduce the calculation time, the fringes imaged on CCD sensor are processed as analog data in the time domain. The fringes are spatial information on a CCD sensor, and can be converted to a synchronous electrical signal by the CCD driving clock pulse at the terminal of CCD output. In the new method, the analog electrical signal, which corresponds to the fringes on the CCD sensor, is analyzed using an electrical circuit in the time domain. The time-instantaneous frequency and phase of the fringes are detected by frequency-demodulating and integrating the signal, respectively. This proposed system can perform high speed fringe analysis operations in 10 ms per raster line of the CCD. The experimental results show that the new fringe analysis has very high speed and is as accurate as the FFT method.

A comparative study is made of phase-unwrapping algorithms that adopt either phase gradients or fringe amplitudes as a reliability measure in the selection of an unwrapping path. To compare with the minimum-phase-gradient spanning-tree algorithm, a maximum cross-amplitude spanning-tree algorithm is proposed, which seeks a spanning tree that maximizes overall edge weights given by the crossamplitudes, i.e., the products of the fringe amplitudes of neighboring pixels. Noise immunity of the cross-amplitude spanning-tree algorithm is demonstrated by experiment and computer simulation.

Beginning with the linear equation of holographic interferometry for small displacements, a technique with a recording of the undeformed and the deformed states of an opaque body on two separate holograms and a modification at the reconstruction is investigated in the general nonlinear case of relatively large strain and large rotation. First, the problem of recovering previously invisible fringes and the following fringe analysis for the strain determination is briefly discussed. Necessary equations from two first derivatives of the optical path difference should ensure, by a careful choice of the modification parameters, at least locally proper spacing and sufficient contrast of the fringes. To enlarge the domain of visibility, the second derivative must also be considered; the remaining parameters should be determined such that the path difference becomes quasi stationary in an extended domain. Here the principal subject is a detailed analysis of this second derivative of the optical path difference, which reveals peculiar properties as a by-product of the mentioned purpose. It contains out-of-plane terms with changes of the surface curvature and in-plane terms with the derivative of the surface dilatation. The latter terms are obtained by the basic integrability equation for curved surfaces. This equation enables, on one hand, the elimination of the variable rotation part of the deformation and shows, on the other hand, a relation to the dislocation theory of continuum mechanics. Three quadratic forms appear besides terms with the geodesic curvature and the first derivative in the final result of the second derivative along any curve. One of the forms contains the deformation of the object surface, the two others imply the virtual deformation of the images due to the modification. The duality property in holographic imaging enables the elimination of a bilinear form. The expression also enables us to analyze the fringe curvature.

A new method of electronic speckle pattern interferometry (ESPI) is introduced. It is a two-stage process. In the first stage a holographic optical element (HOE) is recorded in a usual holographic arrangement. This HOE illuminated later reconstructs an object wave that serves as an ESPI reference wave. Well suited HOEs are produced on photothermoplastic or silver halide media. In the case of silver halide media, both recording and momental monobath photoprocessing of the HOE are performed in presence of an intense polychromatic illumination to meet industrial requirements. Due to the introduction of HOE the second stage, ESPI implementation can be performed with an extremely simple optical setup. The number of optical elements, apart from the video camera, can be drastically reduced to only two elements: a plane mirror and the HOE. High accuracy alignment of the optical elements is not necessary. Our method also enables HOE recording in the ESPI setup practically without modifications. Both experimental results and the ready device are presented. Our optical setup is compact and needs no sophisticated vibration insulation and no dark room, thus it is ideally suited for industrial applications.

A differential absorption lidar (DIAL) system, based on a tunable solid-state Ti:sapphire laser, was developed for nitrogen dioxide monitoring in the blue region. Efficient generation of blue light was realized by sum-frequency mixing between a Ti:sapphire laser, pumped by the second harmonic (SH) of a Nd:YAG laser, and a second Nd:YAG laser. A maximum output pulse energy of 20 mJ at 453 nm was achieved. In order to reduce the error from the change of atmospheric conditions, the laser wavelength was switched on and off resonance in every shot, and the data were averaged over 500 pulse pairs. As an example of measurement, a spatial distribution of nitrogen dioxide emission from a diesel engine was measured by this DIAL system. The detection limit achieved was 0.2 ppm, with a spatial resolution of 12 m.

An alarm system was constructed and tested to demonstrate for the first time an all-optical system that uses electron trapping material with unsupervised learning. The alarm system provides an output when there is a deviation from a time weighted average of a 2-D input image. Classic Hebbian unsupervised learning is used to update the 2-D time weighted average weight array recursively with an all-optical loop. The fabrication of micrometer resolution nanosecond response electron trapping material is described and equations derived to show for the first time that electron trapping materials correctly multiply in parallel elements in a 2-D input image with corresponding elements in a second 2-D weight array. The alarm system equations and associated optic implementation are modified for a binary system instead of a bipolar one because of positivity of intensity. The system uses two electron trapping spatial light rebroadcasters (SLRs), one stores the 2-D weight array and the other the scalar output for synchronization and delay of the all-optical loop. The experiment uses a folded configuration to save cost by using only one image intensifier and liquid crystal light valve for both SLRs. Optical experimental results show the correct functioning of the system.

A possible approach to high track density in optical recording is to reduce the track widths and eliminate the spacing between consecutive tracks. Parallel readback of several tracks and combined equalization of the multitrack readback signals is a viable approach toward reducing the deteriorating effects of interference in such a high-trackdensity system. Multichannel readback using laser diode arrays has been reported in optical recording. An additional advantage of multitrack readback is a high data rate. A novel multichannel decision feedback equalizer to reduce interference both within and across the tracks using 2-D feedback is presented. Simulation results shows good improvement in error-rate performance by using multichannel decision feedback equalization. By this readback method, tracks can be brought closer, thus increasing the areal density.

Pointing errors can compromise the performance of laser systems and cause numerous operational problems. Alignment tolerances for a generic electro-optical system comprising a laser are derived from first principles. The method applies to a sizeable class of problems but is particularly relevant to military applications such as laser target designation and rangefinding. It yields exact or conservative estimates in most cases of practical interest. Various results are explored from the point of view of employment methods and military deployment.

A new texture synthesis-by-analysis method, applying a visually based approach that has some important advantages over more traditional texture modeling and synthesis techniques is introduced. The basis of the method is to encode the textural information by sampling both the power spectrum and the histogram of homogeneously textured images. The spectrum is sampled in a log-polar grid using a pyramid Gabor scheme. The input image is split into a set of 16 Gabor channels (using four spatial frequency levels and four orientations), plus a lowpass residual (LPR). The energy and equivalent bandwidths of each channel, as well as the LPR power spectrum and the histogram, are measured and the latter two are compressed. The synthesis process consists of generating 16 Gabor filtered independent noise signals with spectral centers equal to those of the Gabor filters, whose energy and equivalent bandwidths are calculated to reproduce the measured values. These bandpass signals are mixed into a single image, whose LPR power spectrum and histogram are modified to match the original features. Despite the coarse sampling scheme used, very good results have been achieved with nonstructured textures as well as with some quasiperiodic textures. Besides being applicable to a wide range of textures, the method is robust (stable, fully automatic, linear, and with a fixed code length) and compact (it uses only 69 parameters).

The UV-and-x-ray double-resonance absorption process in 1 mm tryptophan grains was studied. The excited molecular density can be obtained by the use of a three-state model for UV absorption. The dependence of the x-ray transmittance on the UV-laser photon flux using was investigated using the x-ray absorption cross sections obtained by a calculation based on the atomic Hartree-Slater method. It was found that x-ray absorption is increased markedly by the use of a 5-ns UV pulse with a peak photon flux of ~1025 photons cm-2 s-1. Furthermore, the feasibility of x-ray microscopy using double-resonance absorption is considered. It is expected that the images of particular molecules can be obtained selectively with a good signal-to-noise ratio.

The design of a Schwarzschild imaging microscope for soft x-ray applications has been reported by Hoover and Shealy. Based upon a geometrical ray-trace analysis of the residual design errors, diffractionlimited performance at a wavelength of 100 Å was predicted over an object size (diameter) of 0.4 mm. We expand on the analysis of that design by determining the total image degradation due to diffraction, geometrical aberrations, and scattering effects due to residual optical fabrication errors. A linear systems treatment of surface scattering phenomena is used to model the image degradation effects of surface irregularities over the entire range of relevant spatial frequencies. This includes small angle scattering effects due to mid spatial frequency surface errors falling between the traditional ‘‘figure’’ and ‘‘finish’’ specifications. The implementation of this scattering theory as a general performance prediction code is validated by excellent agreement with limited test data for a different Schwarzschild microscope at a wavelength of 73 Å. Finally, image quality predictions are presented parametrically to provide insight into the optical fabrication tolerances necessary to meet desired image quality requirements.

This book provides an overview of current theoretical and experimental research in the area of temporal solitons in optical fibers. These solitons are nondispersive light pulses based on the nonlinearity of the fiber’s refractive index. With the advent of low loss single-mode optical fibers, the applications to long-distance all-optical highbit- rate communications are being vigorously pursued by several laboratories throughout the world.

This PDF file contains the editorial “Book Rvw: Design Issues in Optical Processing," edited by John N. Lee for OE Vol. 35 Issue 08

This PDF file contains the editorial “Ultrafast Diode Lasers” for OE Vol. 35 Issue 07