An integrated high-level hardware/software partitioning methodology

Embedded systems are widely used in many sophisticated applications. To speed the time-to-market cycle, the hardware and software co-design has become one of the main methodologies in modern embedded systems. The most important challenge in the embedded system design is partitioning; i.e. deciding which modules of the system should be implemented in hardware and which ones in software. Finding an optimal partition is hard because of the large number and different characteristics of the modules that have to be considered.     

Applying SMT-based verification to hardware/software partitioning in embedded systems

When performing hardware/software co-design for embedded systems, the problem of which functions of the system should be implemented in hardware (HW) or in software (SW) emerges. This problem is known as HW/SW partitioning. Over the last 10 years, a significant research effort has been carried out in this area. In this paper, we present two new approaches to solve the HW/SW partitioning problem by using verification techniques based on satisfiability modulo theories (SMT). We compare the results using the traditional technique of integer linear programming, specifically binary integer programming and a modern method of optimization by genetic algorithm. The experimental results show that SMT-based verification techniques can be effective in particular cases to solve the HW/SW partition problem optimally using a state-of-the-art model checker based on SMT solvers, when compared against traditional techniques.     

A project management approach to using simulation for cost estimation on large, complex software development projects

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An RKHS approach to robust L2 estimation andsignal detection

The application of RKHS (reproducing kernel Hilbert space) theory to the problems of robust signal detection and estimation is investigated. It is shown that this approach provides a general and unified framework in which to analyze the problems of L² estimation, matched filtering, and quadratic detection in the presence of uncertainties regarding the second-order structure of the random processes involved     

An approach to QRS complex detection using mathematicalmorphology

An approach to QRS complex detection based on mathematical morphology is presented. QRS complexes are detected by the application of a simple morphological operator. This operator works as a peak-valley extractor and it is controlled by the shape of the structuring element. A set (horizontal line segment) is used as a structuring element, resulting in very fast execution times. The accuracy of this approach has been tested using a standard ECG library; a sensitivity of 99.38% and a positive predictivity of 99.48% have been achieved