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This paper describes the details of a National Science Foundation multi-year educational project at the University of Oklahoma (OU). The goal of this comprehensive active-learning and hands-on laboratory program is to develop an interdisciplinary program, in which engineering, geoscience, and meteorology students participate, which forms a community of university scholars. The program is intended to generate a unique, interdisciplinary, research-oriented learning environment that will train future engineers and meteorologists in the full set of competencies needed to take raw radar data to detect weather and aircraft. The program involves new coursework and is oriented around other successful programs to ensure wide distribution by many students and scientists. Supported by the Division of Undergraduate at the NSF, the project began with a Phase II grant in the fall of 2004, which also recently received a Phase II grant to refine the project through 2010. In keeping with the global movement of electronic knowledge delivery via written, as well as visual media, several weblinks have been established for this paper.

In this paper, the development of a low cost fuel cell inverter system is detailed. The approach consists of a three-terminal push-pull dc-dc converter to boost the fuel cell voltage (48 V) to [+ or -]200 VDC. A four switch [insulated gate bipolar transistor (IGBT)] inverter is employed to produce 120-V/240-V, 60-Hz ac outputs. High performance, easy manufacturability, lower component count, safety and cost are addressed. Protection and diagnostic features form an important part of the design. Another highlight of the proposed design is the control strategy, which allows the inverter to adapt to the requirements of the load as well as the power source (fuel cell). A unique aspect of the design is the use of the TMS320LF2407 DSP to control the inverter. Two sets of lead-acid batteries are provided on the high voltage dc bus to supply sudden load demands. Efficient and smooth control of the power drawn from the fuel cell and the high voltage battery is achieved by controlling the front end dc-dc converter in current mode. The paper details extensive experimental results of the proposed design on Department of Energy (DoE) National Energy Technology Laboratory (NETL) fuel cell. Index Terms--Current mode, dc-dc converter, fuel cell.

This paper discusses a real-time digital signal processor (DSP)-based hierarchical neural network classifier capable of classifying both analog and digital modulation signals. A high-performance DSP processor, namely the TMS320C6701, is utilized to implement different kinds of classifiers including a hierarchical neural network classifier. A total of 31 statistical signal features are extracted and used to classify 11 modulation signals plus white noise. The modulation signals include CW, AM, FM, SSB, FSK2, FSK4, PSK2, PSK4, OOK, QAM16, and QAM32. A classification hierarchy is introduced and the genetic algorithm is employed to obtain the most effective set of features at each level of the hierarchy. The classification results and the number of operations on the DSP processor indicate the effectiveness of the introduced hierarchical neural network classifier in terms of both classification rate and processing time. Index Terms--Digital signal processor (DSP) implementation, hierarchical neural network classifier, modulation signal classification.