Numerical Simulations for Geodetic Parameter Estimation from Space VLBI Data

Stochastic processes are employed in this paper to capture the evolution of daily mean temperatures, with the goal of pricing temperature-based weather options. A stochastic harmonic oscillator model is proposed for the temperature dynamics and results of numerical simulations and parameter estimation are presented. The temperature model is used to price a one-month call option and a sensitivity analysis is undertaken to examine how call option prices are affected when the model parameters are varied.

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Wet delay variability calculated from radiometric measurements and its role in space geodetic parameter estimation

Radio Science ◽

10.1029/98rs00551 ◽

1998 ◽

Vol 33 (3) ◽

pp. 719-730 ◽

Cited By ~ 10

Author(s):

Per O. J. Jarlemark ◽

T. Ragne Emardson ◽

Jan M. Johansson

Keyword(s):

Parameter Estimation ◽

Radiometric Measurements ◽

Geodetic Parameter ◽

Delay Variability

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Parameter Estimation of Multicomponent Cubic Phase Signals

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.380-384.3726 ◽

2013 ◽

Vol 380-384 ◽

pp. 3726-3729

Author(s):

Peng Fei Tang ◽

Bin Yuan ◽

Qian Qiang Lin ◽

Zeng Ping Chen

Keyword(s):

Parameter Estimation ◽

Numerical Simulations ◽

Phase Function ◽

Cubic Phase ◽

Chirp Rate ◽

Signal Component ◽

Phase Signal ◽

Cubic Phase Function

This paper presents an algorithm for estimating the parameters of multicomponent cubic phase signals. This algorithm combines the product generalized cubic phase function (PGCPF) and the product cubic phase function (PCPF) which are used to estimate the cubic phase coefficient and chirp rate of the cubic phase signal, respectively. This algorithm starts by estimating the parameters of the signal component with the strongest amplitude. Then removing the signal component whose parameters have been estimated, it proceeds to estimate the next signal component, and so on, until all of the signal components have been estimated. Numerical simulations are carried out to validate the performance of the proposed algorithm.

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Optics-less smart sensors and a possible mechanism of cutaneous vision in nature

Open Physics ◽

10.2478/s11534-009-0132-7 ◽

2010 ◽

Vol 8 (3) ◽

Author(s):

Leonid Yaroslavsky ◽

Chad Goerzen ◽

Stanislav Umansky ◽

H. Caulfield

Keyword(s):

Parameter Estimation ◽

Numerical Simulations ◽

Statistical Parameter ◽

Radiation Detectors ◽

Estimation Theory ◽

Curved Surface ◽

Smart Sensors ◽

Working Principle ◽

Living Organisms ◽

Shed Light

AbstractAlthough optics-less cutaneous (“skin”) vision is not uncommon among living organisms, its mechanisms and capabilities have not been thoroughly investigated. This paper demonstrates, using methods from statistical parameter estimation theory and numerical simulations, that arrays of bare radiation detectors arranged on a planar or curved surface have the ability to perform imaging tasks without any optics at all. The working principle of this type of optics-less sensors and the model developed here for determining their performance may be used to shed light on possible mechanisms, capabilities and evolution of cutaneous vision in nature.

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A Velocity Measurement Method Based on Scaling Parameter Estimation of a Chaotic System

Metrology and Measurement Systems ◽

10.2478/v10178-011-0009-1 ◽

2011 ◽

Vol 18 (2) ◽

pp. 275-282

Author(s):

Lidong Liu ◽

Jifeng Hu ◽

Zishu He ◽

Chunlin Han ◽

Huiyong Li ◽

...

Keyword(s):

Parameter Estimation ◽

Numerical Simulations ◽

Chaotic System ◽

Velocity Measurement ◽

Measurement Method ◽

Chaotic Synchronization ◽

New Method ◽

Target Velocity ◽

Scaling Parameter ◽

Generating System

A Velocity Measurement Method Based on Scaling Parameter Estimation of a Chaotic SystemIn this paper, we propose a new method of measuring the target velocity by estimating the scaling parameter of a chaos-generating system. First, we derive the relation between the target velocity and the scaling parameter of the chaos-generating system. Then a new method for scaling parameter estimation of the chaotic system is proposed by exploiting the chaotic synchronization property. Finally, numerical simulations show the effectiveness of the proposed method in target velocity measurement.

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