876 resultados para coalescing random walk


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This paper presents a 2GS/s 10-bit CMOS digital-to-analog converter (DAC). This DAC consists of a unit current-cell matrix for 6MSBs and another unit current-cell matrix for 4LSBs, trading off between the precision and size of the chip. The Current Mode Logic (CML) is used to ensure high speed, and a double Centro-symmetric current matrix is designed by the Q(2) random walk strategy in order to ensure the linearity of the DAC. The DAC occupies 2.2 x 2.2 mm2 of die area, and consumes 790mw at a single 3.3V power supply.

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This paper describes a 12-bit 300 MHz CMOS DAC for high-speed system applications. The proposed DAC consists of a unit current-cell matrix for 8 MSBs and a binary-weighted array for 4 LSBs. In order to ensure the linearity of DAC, a double Centro symmetric current matrix is designed by using the Q(2) random walk strategy. To minimize the feedthrough and improve the dynamic performance, the drain of the switching transistors is isolated from the output lines by adding two cascoded transistors.

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This paper presents a direct digital frequency synthesizer (DDFS) with a 16-bit accumulator, a 4th-order single-stage pipelined delta-sigma interpolator and a 300MS/s 12-bit current-steering DAC based on Q(2) Random Walk switching scheme. The delta-sigma interpolator is used to reduce the phase truncation error and the ROM size. The measured spurious-free dynamic range (SFDR) is greater than 80 dB for 8-bit phase value and 12-bit sine-amplitude output. The DDFS prototype is fabricated in a 0.35um CMOS technology with core area of 1.11mm(2).

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This paper presents a direct digital frequency synthesizer (DDFS) with a 16-bit accumulator, a fourth-order phase domain single-stage Delta Sigma interpolator, and a 300-MS/s 12-bit current-steering DAC based on the Q(2) Random Walk switching scheme. The Delta Sigma interpolator is used to reduce the phase truncation error and the ROM size. The implemented fourth-order single-stage Delta Sigma noise shaper reduces the effective phase bits by four and reduces the ROM size by 16 times. The DDFS prototype is fabricated in a 0.35-mu m CMOS technology with active area of 1.11 mm(2) including a 12-bit DAC. The measured DDFS spurious-free dynamic range (SFDR) is greater than 78 dB using a reduced ROM with 8-bit phase, 12-bit amplitude resolution and a size of 0.09 mm(2). The total power consumption of the DDFS is 200)mW with a 3.3-V power supply.

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提出了一个刷新率达2GHz的10位电流驱动型数模转换器.在综合了精度与芯片面积等因素之后,该数模转换器使用6+4结构.采用电流型逻辑以提高转换器的速度,并采用Q~2 random walk方法设计了一个双中心对称的电流矩阵,确保数模转换器的线性度.该数模转换器核心版图面积为2.2mm×2.2mm,在3.3V单电压供电的情况下,该芯片功耗为790mW.

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The proposed DAC consists of a unit current-cell matrix for 8MSBs and a binary-weighted array for 4LSBs, trading-off between the precision, speed, and size of the chip. In order to ensure the linearity of the DAC, a double Centro symmetric current matrix is designed by the Q2 random walk strategy. To achieve better dynamic performance, a latch is added in front of the current switch to change the input signal, such as its optimal cross-point and voltage level. For a 12bit resolution,the converter reaches an update rate of 300MHz.

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In this paper, based on Einstein relationship between diffusion and random walk, the electrochemical behavior of a system with a limited number of molecules was simulated and explored theoretically. The transition of the current vs time responses from discrete to continuous was clearly obtained as the number of redox molecules increased from 10 to 10(6).

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For a sphere electrode enclosed in finite-volume electrolyte, the measured current will deviate from the result predicted by the semi-infinite diffusion theory after some time. By random-walk simulation, we compared this time to the one needed for diffusion layer to reach electrolyte boundary, and revealed a clear signal delay of electrochemical current. Further we presented a quantitative description of this delay time. The simulation results suggested that the semi-infinite diffusion theory can even be applied when the theoretical diffusion layer grows to 1.28 electrolyte thicknesses, with an accuracy better than 0.5%. We attributed this time delay to the molecules' finite propagation velocity. Finally, we discussed how this delay can influence and facilitate the following electrochemical detection towards the nanometer and single-cell scale.

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本文研究了移动机器人在湍流环境中定位多个化学羽流源的问题。利用粒子随机行走方法建立动态羽流模型。在此环境中机器人进行梳状搜索并采集羽流数据,使用一种基于后验概率独立假设的改进贝叶斯算法融合这些传感器数据建立一张羽流源位置的概率地图,地图中具有高概率值的栅格指出了羽流源可能的位置。仿真结果说明了该方法的有效性,通过与标准贝叶斯算法的比较说明了该方法优点。

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In a recent seminal paper, Gibson and Wexler (1993) take important steps to formalizing the notion of language learning in a (finite) space whose grammars are characterized by a finite number of parameters. They introduce the Triggering Learning Algorithm (TLA) and show that even in finite space convergence may be a problem due to local maxima. In this paper we explicitly formalize learning in finite parameter space as a Markov structure whose states are parameter settings. We show that this captures the dynamics of TLA completely and allows us to explicitly compute the rates of convergence for TLA and other variants of TLA e.g. random walk. Also included in the paper are a corrected version of GW's central convergence proof, a list of "problem states" in addition to local maxima, and batch and PAC-style learning bounds for the model.

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World-Wide Web (WWW) services have grown to levels where significant delays are expected to happen. Techniques like pre-fetching are likely to help users to personalize their needs, reducing their waiting times. However, pre-fetching is only effective if the right documents are identified and if user's move is correctly predicted. Otherwise, pre-fetching will only waste bandwidth. Therefore, it is productive to determine whether a revisit will occur or not, before starting pre-fetching. In this paper we develop two user models that help determining user's next move. One model uses Random Walk approximation and the other is based on Digital Signal Processing techniques. We also give hints on how to use such models with a simple pre-fetching technique that we are developing.

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We demonstrate that when the future path of the discount rate is uncertain and highly correlated, the distant future should be discounted at significantly lower rates than suggested by the current rate. We then use two centuries of US interest rate data to quantify this effect. Using both random walk and mean-reverting models, we compute the "certainty-equivalent rate" that summarizes the effect of uncertainty and measures the appropriate forward rate of discount in the future. Under the random walk model we find that the certainty-equivalent rate falls continuously from 4% to 2% after 100 years, 1% after 200 years, and 0.5% after 300 years. At horizons of 400 years, the discounted value increases by a factor of over 40,000 relative to conventional discounting. Applied to climate change mitigation, we find that incorporating discount rate uncertainty almost doubles the expected present value of mitigation benefits. © 2003 Elsevier Science (USA). All rights reserved.

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Movements of wide-ranging top predators can now be studied effectively using satellite and archival telemetry. However, the motivations underlying movements remain difficult to determine because trajectories are seldom related to key biological gradients, such as changing prey distributions. Here, we use a dynamic prey landscape of zooplankton biomass in the north-east Atlantic Ocean to examine active habitat selection in the plankton-feeding basking shark Cetorhinus maximus. The relative success of shark searches across this landscape was examined by comparing prey biomass encountered by sharks with encounters by random-walk simulations of ‘model’ sharks. Movements of transmitter-tagged sharks monitored for 964 days (16754km estimated minimum distance) were concentrated on the European continental shelf in areas characterized by high seasonal productivity and complex prey distributions. We show movements by adult and sub-adult sharks yielded consistently higher prey encounter rates than 90% of random-walk simulations. Behavioural patterns were consistent with basking sharks using search tactics structured across multiple scales to exploit the richest prey areas available in preferred habitats. Simple behavioural rules based on learned responses to previously encountered prey distributions may explain the high performances. This study highlights how dynamic prey landscapes enable active habitat selection in large predators to be investigated from a trophic perspective, an approach that may inform conservation by identifying critical habitat of vulnerable species.

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Understanding the mechanisms linking oceanographic processes and marine vertebrate habitat use is critical to effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been shown to associate with oceanographic fronts – physical interfaces at the transitions between water masses – to exploit foraging opportunities resulting from aggregation of zooplankton. However, the scale, significance and variability of these observed associations have not yet been established. Here, we quantify the influence of mesoscale (10s – 100s km) frontal activity on habitat use over timescales of weeks to months. We use animal-mounted archival tracking with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to individual shark movements. We investigate levels of association with fronts occurring over two spatio-temporal scales, (i) broad-scale seasonally persistent frontal zones and (ii) contemporaneous mesoscale thermal and chl-a fronts. Using random walk simulations and logistic regression within an iterative generalised linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Temporally-matched oceanographic metrics also indicate that sharks demonstrate a preference for productive regions, and associate with contemporaneous thermal and chl-a fronts more frequently than could be expected at random. Moreover, we highlight the importance of cross-frontal temperature change and persistence, which appear to interact to affect the degree of prey aggregation along thermal fronts. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the northeast Atlantic.

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Understanding the mechanisms linking oceanographic processes and marine vertebrate habitat use is critical to effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been shown to associate with oceanographic fronts – physical interfaces at the transitions between water masses – to exploit foraging opportunities resulting from aggregation of zooplankton. However, the scale, significance and variability of these observed associations have not yet been established. Here, we quantify the influence of mesoscale (10s – 100s km) frontal activity on habitat use over timescales of weeks to months. We use animal-mounted archival tracking with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to individual shark movements. We investigate levels of association with fronts occurring over two spatio-temporal scales, (i) broad-scale seasonally persistent frontal zones and (ii) contemporaneous mesoscale thermal and chl-a fronts. Using random walk simulations and logistic regression within an iterative generalised linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Temporally-matched oceanographic metrics also indicate that sharks demonstrate a preference for productive regions, and associate with contemporaneous thermal and chl-a fronts more frequently than could be expected at random. Moreover, we highlight the importance of cross-frontal temperature change and persistence, which appear to interact to affect the degree of prey aggregation along thermal fronts. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the northeast Atlantic.