29432247
Low Power Design of the Neuroprocessor
This paper presents the performance analysis for CPL based design of a Low power digital neuroprocessor. We have verified the functionality of the components at the high level using Verilog and carried out the simulations in Silos. The components of the proposed digital neuroprocessor have also been verified at the layout level in LASI. The layouts have then been simulated and analyzed in Winspice for their timing characteristics. The result shows that the proposed digital neuroprocessor consistently consumes less power than other designs of the same function. It can also be seen that the proposed functions have lesser propagation delay and thus higher speed than the other designs.
16989082
A Layered Architecture for NOC Design Methodology
ABSTRACT Multiprocessor system on chip (MPSoC) platform is an innovative trend of System on Chip (SoC) that enhances system performance. Demanding quality of service parameters and performance metrics, especially in mobile applications, are leading to the exploration of even more innovative architectures for SoC. These will have to incorporate highly scalable, reusable, predictable, cost and energy efficient architectures. Network on Chip (NOC) is a key example of this trend. NOC separates computing and communication concerns in an elegant manner. We propose here a seven layered architecture for designing NOC-based systems. Such a platform can separate domain specific issues in separate layers, which will allow for more effective modeling of concurrency and synchronization issues, in an attempt to develop an optimized system. For such a layered architecture, models of computation (MOC) will provide a framework to model various algorithms and activities, while accounting for and exploiting concurrency and synchronization aspects. These MOCs may differ from one to another NOC region. Further, a combination of these MOCs may be needed to truly represent a given NOC region. We have analyzed various models of computation (MOC) suitable for NOC. MLDesigner provides a system level modeling platform which allows one to integrate such MOCs together. We present our efforts and experiences so far.
206717449
Tracking Articulated Motion Using a Mixture of Autoregressive Models
We present a novel approach to modelling the non-linear and time-varying dynamics of human motion, using statistical methods to capture the characteristic motion patterns that exist in typical human activities. Our method is based on automatically clustering the body pose space into connected regions exhibiting similar dynamical characteristics, modelling the dynamics in each region as a Gaussian autoregressive process. Activities that would require large numbers of exemplars in example based methods are covered by comparatively few motion models. Different regions correspond roughly to different action-fragments and our class inference scheme allows for smooth transitions between these, thus making it useful for activity recognition tasks. The method is used to track activities including walking, running, etc., using a planar 2D body model. Its effectiveness is demonstrated by its success in tracking complicated motions like turns, without any key frames or 3D information.
121937998
3D human pose from silhouettes by relevance vector regression
We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor prior labelling of body pans in the image. Instead, it recovers pose by direct nonlinear regression against shape descriptor vectors extracted automatically from image silhouettes. For robustness against local silhouette segmentation errors, silhouette shape is encoded by histogram-of-shape-contexts descriptors. For the main regression, we evaluate both regularized least squares and relevance vector machine (RVM) regressors over both linear and kernel bases. The RVM's provide much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. For realism and good generalization with respect to viewpoints, we train the regressors on images resynthesized from real human motion capture data, and test it both quantitatively on similar independent test data, and qualitatively on a real image sequence. Mean angular errors of 6-7 degrees are obtained - a factor of 3 better than the current state of the art for the much simpler upper body problem.
660603
Algorithms for portfolio management based on the Newton method
We experimentally study on-line investment algorithms first proposed by Agarwal and Hazan and extended by Hazan et al. which achieve almost the same wealth as the best constant-rebalanced portfolio determined in hindsight. These algorithms are the first to combine optimal logarithmic regret bounds with efficient deterministic computability. They are based on the Newton method for offline optimization which, unlike previous approaches, exploits second order information. After analyzing the algorithm using the potential function introduced by Agarwal and Hazan, we present extensive experiments on actual financial data. These experiments confirm the theoretical advantage of our algorithms, which yield higher returns and run considerably faster than previous algorithms with optimal regret. Additionally, we perform financial analysis using mean-variance calculations and the Sharpe ratio.
13564962
Modelling and verification of interworking between SIP and H.323
There are currently two standards for signaling and control of Internet telephone calls, namely ITU-T Recommendation H.323 and the IETF session initiation protocol (SIP). Both protocols provide similar functionality using different mechanisms. Both H.323 and SIP provide interoperability, flexibility and scalability in different aspects and environments. Interworking between SIP and H.323 is essential to ensure full end-to-end connectivity through the network, although the current number of deployed commercial SIP endpoints is relatively small compared to widely deployed H.323 endpoints.To formally specify the SIP-H.323 Interworking, this paper gives a new system model for interworking between SIP and H.323. Five main components of this system are modeled using system description language and message sequence chart: H.323 endpoint, H.323 gatekeeper, SIP-H.323 Interworking facility, SIP server, SIP endpoint. We design and define the internal structure and behavior for each component, which is established for simulating and verifying interworking between SIP and H.323. Under two different configurations that both protocols work within the same administrative domain and that both protocols are operating in separate administrative domains, we use a series of scenarios to show that our model meets the functional specifications outlined in the SIP-H323-Interworking specification documents.
8220547
A tree division approach to support local failure recovery for multicasting in MPLS networks
This paper introduces a novel approach to support local failure recovery in multicast trees. Although, the presented approach can be implemented in any large backbone network that employs multicast communication mode, we concentrate our discussion on MPLS networks. In the proposed approach, a multicast tree is divided into several domains where each domain represents a sub-tree of the original one. Backup paths are built between the root of the domain and each leaf router which is called a border router. Simulation results conducted on two network topologies show the performance of the proposed approach in terms of the total capacity required for reserving the backup paths and in terms of the maximum delay needed to notify about link/node failure. The results have shown that tree division approach compared with global recovery approach reduces the time needed to notify the router that is responsible for switching the traffic to the backup path.