Judy Chen

Ongoing applications of soft computing technologies to real-world problems at Physical Optics Corporation

Soft computing is a set of promising computational tools for solving problems that are inherently well solved by humans but not by standard computing means. This paper presents an overview of R and D activities at Physical Optics Corporation in the area of soft computing. The company has been involved in soft computing for over ten years, and has pioneered several soft-computing methodologies, including fuzzied genetic algorithms and neuro-fuzzy networks. Several practical implementations of soft computing are discussed.

Fuzzified genetic algorithm with prefiltering for adaptive optimization

Genetic algorithm performance has been improved by adaptively modifying genetic operators, and by filtering out recurring chromosomes from the fitness evaluation process. The enhanced genetic algorithm has been applied to neural network topology selection and function optimization. The performance of the algorithm was evaluated in multiple function and problem domains, where it showed superior convergence speed.

Real-time smart optical SAR signal processor

Optoelectronic SAR signal processing for real-time parallel adaptive on-board wide area surveillance and ATR applications is described. The signal processing architecture consists of a coarse ATR processor that performs early detection of small targets to select regions of interest in a large field of view, and a fine ATR processor for accurate classification of selected targets. Both coarse and fine ATR processors apply circular correlation-based algorithms implemented with optical joint transform correlators. Together with associative memory and genetic algorithm composite filtering, this discriminates among similar targets and rejects cluttered backgrounds.

Robust target recognition based on fractal analysis

Fractal image processing technology has been recognized as having great potential in automatic target recognition (ATR) and image compression. In this paper, Physical Optics Corporation demonstrates the feasibility of using a fractal image processing technique as a new and efficient approach for signature, pattern, and object recognition. Using optical Fourier transform and a ring-wedge detection technique, we generate and measure the power spectral density of an input scene. The log-log plot of the power spectral density vs. spatial frequency provides a very valuable signature for each input. Experimental results show that we can successfully discriminate man-made objects from natural objects in input scenes by analyzing signatures obtained this way.

Extended-field-of-view 3D monitor without eyewear

Physical Optics Corporation has developed a unique technology and processes to fabricate a 3D display system that does not require wearing glasses or other eyewear. The authors present the result of true 3D (T3D) monitor development, the third generation T3D being based on a holographic multiplexing screen. The monitor displays 3D autostereoscopic information to three viewers. Holographic multiplexing allows a large number of viewers to see the 3D effect without compromising resolution or having to wear any type of special glasses or goggles. The 3D monitor can deliver high resolution graphics -- 1024 X 480 pixels -- as well as NTSC video in both composite and S-video formats.

Intelligent security system based on neuro-fuzzy multisensor data fusion

This paper presents a real-world application of neurofuzzy processing to a security system with multiple sensor. Integrating fuzzy logic with neural networks, the authors have automated the tasks of sensor data fusion and determination of false/true alarms, which currently rely solely on human monitoring operators, so that they operate in a way similar to human reasoning. This integrated security system includes a set of heterogeneous sensor. To take advantage of each sensors strengths, they are positioned and integrated for side, accurate, economical coverage. The system includes real-time tracking cameras functioning as true digital motion detectors with the capability of approximating the size, direction, and number of intruders. The system is also capable of real-time image segmentation based on motion, and of image recognition based on neural networks.

Fuzzy controlled neural network for sensor fusion with adaptability to sensor failure

Artificial neural networks have proven to be powerful tools for sensor fusion, but they are not adaptable to sensor failure in a sensor suite. Physical Optics Corporation (POC) presents a new sensor fusion algorithm, applying fuzzy logic to give a neural network real-time adaptability to compensate for faulty sensors. Identifying data that originates from malfunctioning sensors, and excluding it from sensor fusion, allows the fuzzy neural network to achieve better results. A fuzzy logic-based functionality evaluator detects malfunctioning sensors in real time. A separate neural network is trained for each potential sensor failure situation. Since the number of possible sensor failure situations is large, the large number of neural networks is then fuzzified into a small number of fuzzy neural networks. Experimental results show the feasibility of the proposed approach -- the system correctly recognized airplane models in a computer simulation.

Ultrahigh-speed processor using optical interconnects

Optical interconnects have been designed, fabricated, and tested, and a graphics processor based on field-programmable gate arrays has been designed. The board-to-board connection approach is based on multi-channel integrated optical waveguides with novel optoelectronic active connectors, allowing multiple simultaneous data transfers among many boards. Data is transferred from chip to chip through optical data channels within an integrated chip. For electronic processing systems, we developed a preliminary design for a multiprocessor system suitable for both single instruction multiple data and multiple instruction multiple data, and using video random access memory and static random access memory for main memory, look-up table processing, and display interface.

Optoelectronic interconnect-based multiprocessing systems using microprism arrays

An optical communication/switching system with data speeds well beyond any state-of-the-art electronic board-to-board computer interconnect is proposed. This interconnect is based on the use of microprism arrays to achieve large-scale, wideband interconnections for optoelectronic systems.

Electronic multiprocessor with radiation-hardened optical interconnects

Optical interconnects will play an increasingly significant role in future space applications, because of their high transmission bandwidth potential and radiation hardness. This paper presents the development results of a hybrid optoelectronic system comprising four electronic processing boards that communicate through an optical 3 by 3 non- blocking crossbar switch. Each processing board contains Tx and Rx modules pigtailed to multimode fibers. An optical fan-out of 1-to-3 is implemented by means of a holographic grating. The fan-in is implemented as a lens array. The system has been tested using dedicated automatic target recognition (ATR) software, and space testing is planned.