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We propose computational-lock, a technique for accelerating frequency and phase-acquisition in all-digital PLLs during cold-start and re-lock. A wide-dynamic range, high resolution TDC is also proposed to further support the technique. Resulting lock-time improvements are evaluated through 50,000 repeated measurements of 65nm CMOS test-chips. Mean lock-times of 16Trefcik and 12Trefcik for cold-start...
In wide area Layer 2 (L2) networks, there is a problem that broadcast packets for address resolution fill up link capacities. As a result, address resolution using Address Resolution Protocol (ARP), which uses broadcasts, cannot be used in wide area L2 networks. A conventional research has proposed an architecture using Distributed Hash Table (DHT) and ARP cache for reducing broadcasts. However, since...
In this paper we examine the use of trust metrics for punishing dishonest (cheating) and malicious (griefing) behavior in peer-to-peer massively multiplayer online games (MMOG’s). In particular, we first replicate the work of Goodman and Verbrugge and then propose a metric of our own. Our approach uses a reinforcement learning trust metric that can more rapidly and accurately detect dishonest and...
Currently, researchers use simulators to experimenttheir innovation on emerging non-volatile memory. Unfortunately, simulation method is both time-consuming andare hard to debug. In this paper, we present a non-volatile memory emulatorwhich enables system-level research on emerging memory. Ouremulator uses performance monitoring units on off-the-shelfprocessors to implement an accurete performance...
In a previous publication by the same authors, a computational design system was described that identifies aesthetical color combinations. In that work the type of color aesthetics pursued was to be determined prior to the design representing a given design objective. Complementing the previous study, in this work, the type of color aesthetics that is most suitable for a given scene at hand is pursued...
Unmanned Aerial Vehicles (UAVs) have been used in a wide range of applications, due to high availability and low cost of their core components. One subject of research in the UAV field is the formation flying of a group of aircraft. In this paper, it is described the problem formulation for a formation of UAVs and the control law used to keep the aircraft in position. Following the theoretic model...
This paper presents an open-source object-oriented MATLAB toolkit for control system design and system simulation. The objective of the toolkit is to reduce the time required for the design and validation of a control architecture while at the same time increasing the reliability, modularity, and reusability of each of its components and fostering collaborative design and sharing of the developed...
Software architects devote substantial efforts to find the most fitting architectural description for their system, which should not only specify its structure, but is also required to meet multiple, simultaneous quality criteria. Evolutionary computation has recently demonstrated to provide insightful support during the design phase by automatically deciding how to organise internal software components...
The monitoring of the load assumes a fundamental role in contracting of locational economic amounts of the Transmission Network Use of System (TNUoS) tariff, in this way, it becomes attractive to use computational models of demand forecasting as tools, subsidizing more precise estimates of investments and enabling the attendance of the Reliability. In this context, the present work demonstrates a...
The bound to factor large integers is dominated by the computational effort to discover numbers that are smooth, typically performed by sieving a polynomial sequence. On a von Neumann architecture, sieving has log-log amortized time complexity to check each value for smoothness. This work presents a neuromorphic sieve that achieves a constant time check for smoothness by exploiting two characteristic...
In this contribution an image classification by uncoupled Cellular Nonlinear Networks (CNN) is proposed and evaluated on typical datasets, like CIFAR-10 and MNIST. The algorithm is based on the application of backpropagation for the training of synaptic coupling weights and is capable of binary classification by means of a threshold-based classifier. The design is inspired by recent deep neural network...
In this paper, we propose a (cell) load-aware approach to performing the downlink coordinated multi-point joint transmission (JT-CoMP) scheme in a dense heterogeneous cellular network (HetNet) consisting M tiers of different kinds of base stations (BSs). Inspiring from the fact that there could exist a considerable number of the void BSs in a dense HetNet that are not associated by any users, this...
Fast-paced innovation in the embedded systems domain puts an ever increasing pressure on effective software development methods, leading to the growing popularity of Model-Based Design (MBD). In this context, a proper choice of modeling languages and related tools — depending on design goals and problem qualities — is crucial to make the most of MBD benefits. In this paper, a comparison between two...
This paper presents a non-uniform sampling analog-to-digital converter (ADC) architecture using an adaptive level-crossing technique. The architecture can be dynamically configured through three parameters that allow the user to match the ADC to the signal to be acquired or to application constraints. When applied to sparse signals, this architecture outperforms uniform sampling architectures. In...
This work tackles the seldom discussed task of predicting chaotic time series generated by dynamic systems with evolving parameters. Representative chaotic time series produced by different system dimensions are introduced with a critical parameter linearly depending on time. The evolving character of systems are qualitatively studied by phase portraits. We assess the predictability of different fuzzy...
Neural networks are a powerful function approximation tool which has the ability to model any function with arbitrary precision. For any function as a black box, it is able to reconstruct the function given the target and the input data. However, there are problems where the target is at least partially unknown. In such cases it is impossible for a traditional neural network to compute the gradient...
Emerging neural hardware substrates, such as IBM's “TrueNorth” neurosynaptic system, can provide an appealing platform for deploying numerical algorithms. For example, a recurrent Hopfield neural network can be used to solve for the Moore-Penrose matrix inverse, which enables a broad class of linear optimizations to be solved efficiently, with very low energy cost. However, deploying numerical algorithms...
The combination of Battery-Ultracapacitor, as a Hybrid Energy Storage System (HESS) controlled with a bidirectional buck-boost converter for light electric vehicles is presented in this paper. By combining these two energy storage elements an efficient supply system can be obtained. A bidirectional Buck-Boost converter is used to control the energy transfer between the elements of the HESS and the...
Stencil computation arises from a broad set of scientific and engineering applications and often plays a critical role in the performance of extreme-scale simulations. Due to the memory bound nature, it is a challenging task to opti- mize stencil computation kernels on modern supercomputers with relatively high computing throughput whilst relatively low data-moving capability. This work serves as...
A distributed virtual environment (DVE) consists of multiple network nodes (servers), each of which can host many users that consume CPU resources on that node and communicate with users on other nodes. Users can be dynamically migrated between the nodes, and the ultimate goal for the migration policy is to minimize the average system response time perceived by the users. In order to achieve this,...
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