The application of VHDL (VHSIC hardware description language) in the design and development of a custom DSP (digital signal processing) complex-to-magnitude circuit is described. The circuit produces the magnitude of ...
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The application of VHDL (VHSIC hardware description language) in the design and development of a custom DSP (digital signal processing) complex-to-magnitude circuit is described. The circuit produces the magnitude of a complex number using an approximation algorithm. The target implementation is a bit-serial architecture using a set of primitive operators for DSP design. The algorithm and architecture are investigated at the word level using the real-number type, and the results are applied to the bit level. It is found that VDHL provides strong support and clear documentation for each level of abstraction.
Analyzing the safety of automotive systems at the application level is -especially challenging as often very complex or even incomplete models are available. The authors combine formal reasoning with simulation data t...
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Analyzing the safety of automotive systems at the application level is -especially challenging as often very complex or even incomplete models are available. The authors combine formal reasoning with simulation data to effectively -validate safety or estimate worst case situations of automotive control systems.
It is well known that de offsets degrade the performance of analog adaptive filters. In this paper, the effects of de offsets on four variations of the stochastic gradient algorithm are analyzed. Assuming a Gaussian p...
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It is well known that de offsets degrade the performance of analog adaptive filters. In this paper, the effects of de offsets on four variations of the stochastic gradient algorithm are analyzed. Assuming a Gaussian probability distribution for the input signal and error signal, the output mean squared error (MSE) performance in the presence of de offsets is evaluated for each of the algorithms. The theoretical work is compared with computer simulations and the results, together with convergence properties of each of the algorithms and their respective hardware requirements, are used in selecting the most appropriate algorithm. Although a Gaussian input distribution is assumed, it may reasonably be inferred that the critical results obtained should also hold for other input distributions.
A method for applying combinatorial optimization algorithms to Energy Storage System (ESS) scheduling is presented in this paper. Scheduling is essential for the integration of ESS in electrical networks at grid level...
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A method for applying combinatorial optimization algorithms to Energy Storage System (ESS) scheduling is presented in this paper. Scheduling is essential for the integration of ESS in electrical networks at grid level or at consumer level to achieve the objectives of integration such as constraint management or energy cost reduction and for efficient storage dispatch. It also shows that for a time-of-use (ToU) tariff scheme based on the shape of the demand profile with higher prices tied to peak periods, effective load-leveling, and peak demand reduction always leads to energy cost reduction. While other methods usually require more information such as generation cost curves or ToU tariffs to schedule ESS, the proposed method uses only demand profile information and ESS parameters to achieve load-leveling and peak demand reduction and also considers the entire optimization time horizon. This is done by combining heuristic bin packing and subset sum algorithms with specific modifications to the standard forms and through transformations. A case study is presented in which the algorithm is used to schedule household ESS with repurposed electric vehicle batteries and the results are compared to a demand response scheme on the same setup.
Networks of linear units are the simplest kind of networks, where the basic questions related to learning, generalization, and self-organization can sometimes be answered analytically, We survey most of the known resu...
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Networks of linear units are the simplest kind of networks, where the basic questions related to learning, generalization, and self-organization can sometimes be answered analytically, We survey most of the known results on linear networks, including: 1) backpropagation learning and the structure of the error function landscape, 2) the temporal evolution of generalization, and 3) unsupervised learning algorithms and their properties, The connections to classical statistical ideas, such as principal component analysis (PCA), are emphasized as well as several simple but challenging open questions, A few new results are also spread across the paper, including an analysis of the effect of noise on backpropagation networks and a unified view of all unsupervised algorithms.
A held matching technique is used to analyze an N-way divider which includes a radial cavity with a coaxial central port and H-plane coupled rectangular waveguide output ports, Dielectric coated and disc ended probes ...
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A held matching technique is used to analyze an N-way divider which includes a radial cavity with a coaxial central port and H-plane coupled rectangular waveguide output ports, Dielectric coated and disc ended probes at the central port are considered. The analysis is divided into two parts, Part one is associated with the modeling of the central port and part two is concerned with the modeling of the waveguide peripheral ports. The analysis is simplified by assuming that the interaction between the central port and the peripheral ports is by means of axially symmetric radial waves which are uniform with cavity's height. Based on this analysis, algorithms are developed for calculating the scattering parameters of this structure using a PC. These algorithms show good agreement when tested against a finite element package (HFSS) and against measurements.
We analyzed the delay failure induced in standard-cell ASICs by total-ionizing dose. We developed a novel cell-level fault model for delay failures. We used this fault model to identify worst-case test vectors (WCTV) ...
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We analyzed the delay failure induced in standard-cell ASICs by total-ionizing dose. We developed a novel cell-level fault model for delay failures. We used this fault model to identify worst-case test vectors (WCTV) for delay failures induced in ASIC devices exposed to total ionizing dose. The fault model was experimentally validated using SPICE simulation and total dose data. We introduced a fast search algorithm based on directed graph and genetic algorithms to help identify WCTV for large ASICs within reasonable search time. The methodology was validated using ASIC test chip and Cobalt 60 facility.
The performance of gradient search adaptive filters, such as the least mean squares (LMS) algorithm, may degrade badly when the filter is subjected to input signals which are corrupted by impulsive interference. The m...
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The performance of gradient search adaptive filters, such as the least mean squares (LMS) algorithm, may degrade badly when the filter is subjected to input signals which are corrupted by impulsive interference. The median 1,MS (MLMS) adaptive filter is designed to alleviate this problem by protecting the filter coefficients from the impact of the impulses. MLMS is a modification of LMS, obtained by applying a median operation to the raw gradient estimates of the mean squared error performance surface. An analysis of the MLMS algorithm is provided for the class of independent and identically distributed inputs. For these inputs we establish exponential convergence of the MLMS algorithm. The rate of convergence is shown to depend on order statistics of the input, but unlike that for LMS shows little dependence on characteristics of the impulsive interference. The steady state performance of the LMS and MLMS is also examined. The average deviation of the parameter estimates from their optimal values caused by the arrival of an impulse is assessed. This analysis indicates a significantly improved performance for MLMS compared to LMS. Analytic predictions for both convergence and steady state behavior are supported by simulations.
Presents a heuristic search algorithm inspired by evolutionary methods to solve the all-terminal network design problem when considering cost and reliability. Network topology; Failure of links as mutually independent...
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Presents a heuristic search algorithm inspired by evolutionary methods to solve the all-terminal network design problem when considering cost and reliability. Network topology; Failure of links as mutually independent; Connectivity check for a spanning tree; Set of nodes and links.
A distributed computation consists of a set of processes chat cooperate and compete to achieve a common goal. These processes do not share a common global memory and communicately solely by passing messages communicat...
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A distributed computation consists of a set of processes chat cooperate and compete to achieve a common goal. These processes do not share a common global memory and communicately solely by passing messages communication network. The communication delay is finite but unpredictable. A process's actions are modeled as three types of events: internal, message send, and message receive. An internal event affects only the process at which it occurs, and the events at a process are linearly ordered by their order of occurrence. Send and receive events signify the flow of information between processes and establish causal dependency from the sender process to the receiver process. Consequently, the execution of a distributed application results in a set of distributed events produced by the process. The causal precedence relation induces a partial order on the events of a distributed computation. Causality among events, more formally the causal precedence relation, is a powerful concept for reasoning, analyzing, and drawing inferences about a distributed computation. Knowledge of the causal precedence relation between processes helps programmers, designers, and the system itself solve a variety of problems in distributed computing. The notion of time is basic to capturing the causality between events. Distributed systems have no built-in physical time and can only approximate it. However, in a distributed computation, both the progress and the interaction between processes occur in spurts. Consequently, logical clocks can be used to accurately capture the causality relation between events. This article presents a general framework of a system of logical clocks in distributed systems and discusses three methods-scalar, vector, and matrix-for implementing logical time in these systems.
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