725 research outputs found
Maximising information transfer through nonlinear noisy devices
No full text© 2003 COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.Consider an array of parallel comparators (threshold devices) receiving the same input signal, but subject to independent noise, where the output from each device is summed to give an overall output. Such an array is a good model of a number of nonlinear systems including flash analogue to digital converters, sonar arrays and parallel neurons. Recently, this system was analysed by Stocks in terms of information theory, who showed that under certain conditions the transmitted information through the array is maximised for non-zero noise. This phenomenon was termed Suprathreshold Stochastic Resonance (SSR). In this paper we give further results related to the maximisation of the transmitted information in this system.Mark D. McDonnell, Nigel G. Stocks, Charles E. M. Pearce, and Derek Abbot
Stochastic resonance in electrical circuits—II: Nonconventional stochastic resonance.
No full textStochastic resonance (SR), in which a periodic signal in a nonlinear system can be amplified by added noise, is discussed. The application of circuit modeling techniques to the conventional form of SR, which occurs in static bistable potentials, was considered in a companion paper. Here, the investigation of nonconventional forms of SR in part using similar electronic techniques is described. In the small-signal limit, the results are well described in terms of linear response theory. Some other phenomena of topical interest, closely related to SR, are also treate
The precautionary demand for commodity stocks
No full textThis paper develops a theory of the precautionary demand for commodity stocks. It suggests that commodity stocks are held for precautionary purposes by producers, consumers, and intermediate processors, while speculators hold stocks on the expectation of capital gains from a subsequent price rise. Producer and consumer stocks usually account for the largest share of commercial stocks held at any point in time. For example, at the end of 1990, stocks held by producers and consumers of copper were 72 percent of all commercial stocks of the market economy countries. Yet, the theory explaining the behavior of this class of stocks has not progressed much beyond the concept of convenience yield, first introduced by Kaldor (1939). This paper proposes an alternative theory. Holding of stocks by producers and consumers is viewed as precautionary behavior towards output and price risks. As a theory of behavior towards risks, the precautionary stock demand model encompasses speculative demand by both producers and consumers. Furthermore, both stocks and futures are treated as precautionary instruments, in contrast to the dichotomy that only stocks provide convenience yield while futures are hedging instruments.Access to Markets,Markets and Market Access,Economic Theory&Research,Environmental Economics&Policies,Non Bank Financial Institutions
Stochastic resonance in electrical circuits—I: Conventional stochastic resonance.
No full textStochastic resonance (SR), a phenomenon in which a periodic signal in a nonlinear system can be amplified by added noise, is introduced and discussed. Techniques for investigating SR using electronic circuits are described in practical terms. The physical nature of SR, and the explanation of weak-noise SR as a linear response phenomenon, are considered. Conventional SR, for systems characterized by static bistable potentials, is described together with examples of the data obtainable from the circuit models used to test the theory
Effectiveness of seasonal influenza vaccine in Australia, 2015: an epidemiological, antigenic and phylogenetic assessment
No full textAbstract not availableJames E. Fielding, Avram Levy, Monique B. Chilver, Yi-Mo Deng, Annette K. Regan, Kristina A. Grant, Nigel P. Stocks, Sheena G. Sulliva
Safety of Ceasing Aspirin Used Without a Clinical Indication After Age 70 Years: A Subgroup Analysis of the ASPREE Randomized Trial
No full textLettersAbstract not availableMark R. Nelson, Galina Polekhina, Robyn L. Woods, Christopher M. Reid, Andrew M. Tonkin, Rory Wolfe, Anne M. Murray, Brenda Kirpach, Michael E. Ernst, Jessica E. Lockery, Raj C. Shah, Nigel Stocks, Suzanne G. Orchard, Zhen Zho
Optimal quantization and suprathreshold stochastic resonance
No full text©2005 COPYRIGHT SPIE--The International Society for Optical EngineeringIt is shown that Suprathreshold Stochastic Resonance (SSR) iseffectively a way of using noise to perform quantization or lossysignal compression with a population of identical threshold-baseddevices. Quantization of an analog signal is a fundamentalrequirement for its efficient storage or compression in a digitalsystem. This process will always result in a loss of quality,known as distortion, in a reproduction of the original signal. Thedistortion can be decreased by increasing the number of statesavailable for encoding the signal (measured by the rate, or mutualinformation). Hence, designing a quantizer requires a tradeoffbetween distortion and rate. Quantization theory has recently beenapplied to the analysis of neural coding and here we examine thepossibility that SSR is a possible mechanism used by populationsof sensory neurons to quantize signals. In particular, we analyzethe rate-distortion performance of SSR for a range of input SNR'sand show that both the optimal distortion and optimal rate occursfor an input SNR of about 0 dB, which is a biologically plausiblesituation. Furthermore, we relax the constraint that allthresholds are identical, and find the optimal threshold valuesfor a range of input SNRs. We find that for sufficiently smallinput SNRs, the optimal quantizer is one in which all thresholdsare identical, that is, the SSR situation is optimal in this case.Mark D. McDonnell, Nigel G. Stocks, Charles E. M. Pearce, and Derek Abbot
A Buffer Stocks Model for Stabilizing Price in Duopoly-Like Market
No full textThis paper presents the staple-food distribution problem in agro-industry. There is a great difference
of staple-food supplies in the harvest-season and in the planting-season meanwhile the demand is relatively
constant. This situation will trigger price-volatility and shortage of staple-food, and it causes opportunity-losses for the stakeholders (producer, consumer, wholesaler/trader, and the government). For stabilizing the
price, the government has several stabilization policies; one of them is market-intervention policy by using
buffer-stocks schemes. The market-intervention policy should be utilized for improving producer’s profit, for
cutting consumer’s expenditure, and for sustaining wholesaler’s margin-profit by implementing price-support
and price-stabilization. In duopoly-like market, we assume that there are only two market-players in the
distribution system. The objective of this research is to determine the instruments for operating Market-Intervention Program which consist of the quantity, time, and price of the buffer-stocks schemes. The problem
was solved using 3 approaches. First, a comparative cost/benefit analysis between free-market and
intervention-market can be used to formulate the objective function of each stakeholders. Second, the
integration of optimization model and econometrics model were use to develop the decision-variables subject
to the expectation of stakeholders, the buffer-stocks requirement, and the dynamics price equilibrium
properties. Third, model market with Inventory was applied for solving the market-price equilibrium. The
result could be used to analyze such the staple-food distribution system, incorporating the configuration of
duo-producers, duo market-buyers, and duo-consumers.
Keywords: buffer-stocks, duopoly-like market, market-intervention program, model market with inventory,
and staple-food distribution system
Analog to digital conversion using suprathreshold stochastic resonance
No full text© 2005 COPYRIGHT SPIE--The International Society for Optical Engineering Copyright 2004 Society of Photo-Optical Instrumentation Engineers. This paper was published in Smart Structures, Devices, and Systems II, edited by Said F. Al-Sarawi, Proceedings of SPIE Vol. 5649 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.We present an analysis of the use of suprathreshold stochastic resonance for analog to digital conversion. Suprathreshold stochastic resonance is a phenomenon where the presence of internal or input noise provides the optimal response from a system of identical parallel threshold devices such as comparators or neurons. Under the conditions where this occurs, such a system is effectively a non-deterministic analog to digital converter. In this paper we compare the suprathreshold stochastic resonance effect to conventional analog to digital conversion by analysing the rate-distortion trade-off of each.Mark D. McDonnell, Nigel G. Stocks, Charles E. M. Pearce, and Derek Abbot
How to use noise to reduce complexity in quantization
No full text© 2006 COPYRIGHT SPIE--The International Society for Optical EngineeringConsider a quantization scheme which has the aim of quantizing a signal into N+1 discrete output states. The specification of such a scheme has two parts. Firstly, in the encoding stage, the specification of N unique threshold values is required. Secondly, the decoding stage requires specification of N+1 unique reproduction values. Thus, in general, 2N+1 unique values are required for a complete specification. We show in this paper how noise can be used to reduce the number of unique values required in the encoding stage. This is achieved by allowing the noise to effectively make all thresholds independent random variables, the end result being a stochastic quantization. This idea originates from a form of stochastic resonance known as suprathreshold stochastic resonance. Stochastic resonance occurs when noise in a system is essential for that system to provide its optimal output and can only occur in nonlinear systems--one prime example being neurons. The use of noise requires a tradeoff in performance, however, we show that even very low signal-to-noise ratios can provide a reasonable average performance for a substantial reduction in complexity, and that high signal-to-noise ratios can also provide a reduction in complexity for only a negligible degradation in performance.Mark D. McDonnell, Nigel G. Stocks, Charles E.M. Pearce, and Derek Abbot
- …
