Abstract-Logic optimization is the step of the very large scale integration (VLSI) design cycle where the designer performs modifications on a design to satisfy different constraints such as area, power, or delay. Recently, automated test pattern generation (ATPG)-based design rewiring techniques for technology-dependent logic optimization have gained increasing popularity. In this paper, the authors propose a new operational framework to design rewiring that uses ATPG and diagnosis algorithms. They also examine its complexity requirements and discuss different implementation tradeoffs. To perform this study, the authors reduce the problem of design rewiring to the process of injecting a redundant set of multiple pattern faults. This formulation arrives at a new set of results with theoretical and practical applications. Experiments demonstrate the competitiveness of the approach and motivate future work in the area.

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With security and surveillance, there is an increasing need to process image data efficiently and effectively either at source or in a large data network. Whilst a Field-Programmable Gate Array has been seen as a key technology for enabling this, the design process has been viewed as problematic in terms of the time and effort needed for implementation and verification. The work here proposes a different approach of using optimized FPGA-based soft-core processors which allows the user to exploit the task and data level parallelism to achieve the quality of dedicated FPGA implementations whilst reducing design time. The paper also reports some preliminary progress on the design Roger Woods flow to program the structure. An implementation for a Histogram of Gradients algorithm is also reported which shows that a performance of 328 fps can be achieved with this design approach, whilst avoiding the long design time, verification and debugging steps associated with conventional FPGA implementations.

Several new methods for the digital discrimination of neutrons and gamma-rays in a mixed radiation field are presented. The methods introduced discriminate neutrons and gamma rays successfully in the digital domain. They are mathematically simple and exploit samples during the life time of the pulse, hence appropriate for field measurements. All these methods are applied to a set of mixed neutron and photon signals from a stilbene scintillator and their discrimination qualities are compared.

In this paper, we present the results of digital processing of pulses produced by several types of detectors. We introduce a new high quality discrimination method, and the output from this new method is compared with those from classic methods. Also, a new function to determine separation quality of various discrimination methods is defined in this paper. Our results show how the quality of the particle type identification depends on the sampling rate as well as the method of sampled data processing.