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High-level synthesis (HLS) tools are now capable of generating high-quality RTL codes for a number of programs. Nevertheless, for best performance aggressive program transformations are still required to exploit data reuse and enable communication/computation overlap. The polyhedral compilation framework has shown great promise in this area with the(More)
High level synthesis (HLS) is an important enabling technology for the adoption of hardware accelerator technologies. It promises the performance and energy efficiency of hardware designs with a lower barrier to entry in design expertise, and shorter design time. State-of-the-art high level synthesis now includes a wide variety of powerful optimizations(More)
This paper considers an output feedback learning control for a class of uncertain nonlinear systems with flexible components. The distinct time delay caused by system flexibility leads to the phase lag phenomenon and low system bandwidth. Therefore, the tracking problem of such systems is very difficult and challenging. To improve the tracking performance(More)
A Fourier neural network (FNN) based control scheme is presented in this paper for tracking control of a class of unknown nonlinear systems. The FNN employs orthogonal complex Fourier exponentials as the basis functions, and therefore the FNN has a clear physical meaning and the network topology is easily determined. Due to the orthogonality of the basis(More)
With the prevalence of System-on-Chips there is a growing need for automation and acceleration of the design process. A classical approach is to take a C/C++ specification of the application, convert it to a SystemC (or equivalent) description of hardware implementing this application, and perform successive refinement of the description to improve various(More)
This paper presents an algorithm for automatic video object planes extraction from coarse to fine. For the case of single moving object in a scene, block-based segmentation defines regions of foreground, background and boundary blocks. Then, the segmentation problem is formulated as an energy minimization problem which is settled by using graph cut(More)
An adaptive Fourier neural network (AFNN) control scheme is presented in this paper for the control of a class of uncertain nonlinear systems. Based on Fourier analysis and neural network (NN) theory, AFNN employs orthogonal complex Fourier exponentials as the activation functions. Due to the clear physical meaning of the neurons, the determination of the(More)
A new iterative learning control approach based on Fourier neural network (FNN) is presented for the tracking control of a class of nonlinear systems with deterministic uncertainties. The proposed controller consists of two loops. The inner loop is a feedback control action that decreases system variability and reduces the influence of random disturbances.(More)
Web service is subject to frequent changes during its lifecycle. Web service evolution is a widely discussed topic. Many related problems have also been generated from Web service evolution such as Web service adaptation, Web service versioning and Web service change management. To treat with these issues efficiently, a complete evolution model for Web(More)
Under the constantly evolving requirements from the consumers and competition pressure from the peers, Web Service providers are always striving to improve their services through publishing new versions. As more enterprises chose to embrace SOA, the frequent updates of Web services and increasing distributed environments have resulted in major challenges(More)