Stochastic resonance (SR) is studied in a gain-noise model of a single-mode laser driven by a coloured pump noise and a quantum noise with cross-correlation between real and imaginary parts under a direct signal mod...
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Stochastic resonance (SR) is studied in a gain-noise model of a single-mode laser driven by a coloured pump noise and a quantum noise with cross-correlation between real and imaginary parts under a direct signal modulation. By using a linear approximation method, we find that the SR appears during the variation of signal-to-noise ratio (SNR) separately with the pump noise self-correlation time τ, the noise correlation coefficient between the real part and the imaginary part of the quantum noise λq, the attenuation coefficient γ' and the deterministic steady-state intensity I0. In addition, it is found that the SR can be characterized not only by the dependence of SNR on the noise variables of and λq, but also by the dependence of SNR on the laser system variables of γ and I0. Thus our investigation extends the characteristic quantity of SR proposed before.
Due to the zero dispersion point at 1.3μm in optical fibres, 1.3-μm InGaAsP/InP laser diodes have become main light sources in fibre communication systems recently. Influences of quantum noises on direct-modulated p...
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Due to the zero dispersion point at 1.3μm in optical fibres, 1.3-μm InGaAsP/InP laser diodes have become main light sources in fibre communication systems recently. Influences of quantum noises on direct-modulated properties of single-mode 1.3-μm InGaAsP/InP laser diodes are investigated in this article. Considering the carrier and photon noises and the cross-correlation between the two noises, the power spectrum of the photon density and the signal-to-noise ratio (SNR) of the direct-modulated single-mode laser system are calculated using the linear approximation method. We find that the stochastic resonance (SR) always appears in the dependence of the SNR on the bias current density, and is strongly affected by the cross-correlation coefficient between the carrier and photon noises, the frequency of modulation signal, and the photon lifetime in the laser cavity. Hence, it is promising to use the SR mechanism to enhance the SNR of direct-modulated InGaAsP/InP laser diodes and improve the quality of optical fibre communication systems.
Stochastic resonance (SR) for bias signal modulation is studied in a single-mode laser system. By investigating a gain-noise model driven by correlated pump noise and quantum noise, we find that, whether the correlati...
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Stochastic resonance (SR) for bias signal modulation is studied in a single-mode laser system. By investigating a gain-noise model driven by correlated pump noise and quantum noise, we find that, whether the correlation coefficient between both the noises is positive or negative, SR always appears in the dependence of signal-to-noise ratio (SNR) upon the noise correlation time and the frequency of the modulation signal. However, only when the correlation coefficient between both noises is negative can SR occur in the dependence of SNR upon the quantum noise intensity and pump noise intensity, while when the correlation coefficient between both noises is positive, it shows monotonically.
By using the linear approximation method, the output power spectrum is calculated for a single-mode laser driven by coloured pump and quantum noises with coloured correlation. We have observed that the configuration o...
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By using the linear approximation method, the output power spectrum is calculated for a single-mode laser driven by coloured pump and quantum noises with coloured correlation. We have observed that the configuration of the output power spectrum is complicated: that is, it can be of single peak, two peaks or three peaks. The configurations of the power spectrum can be transformed from one into another by changing the cross-correlation time, the cross-correlation coefficient between the two noises and pump noise intensity.
This study aimed to compare two diameter distribution models in Eucalyptus grandis x Eucalyptus urophylla submitted to thinning;and evaluate the influence of two adjustment methods of probability density functions on ...
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This study aimed to compare two diameter distribution models in Eucalyptus grandis x Eucalyptus urophylla submitted to thinning;and evaluate the influence of two adjustment methods of probability density functions on the quality of the diameter structure projections. The data used in this study came from an experiment on thinning of eucalyptus clones, located in the northeast region of the state of Bahia. The measurements were made at the ages 27, 40, 50, 58, 61, 76, 87, 101, 112, 122, 137, 147, 158 and 165 months, with thinnings carried out at 58 and 142 months. Two diameter distribution models were used to prognosticate the diametric structures of the stands, starting from an observed distribution at ages 27 (before first thinning), 61 (after first thinning) and 147 (after second thinning) months. Three systems were obtained according to the adjusting method of the Weibull function: System 1, using the linearapproximation;Systems 2 and 3, using the maximum likelihood. The goodness of fit of prognosticated structures in relation to those observed was verified by the Kolmogorov-Smirnov test at 5% of significance. System 2 was the most suitable for practical applications for thinning in eucalypts. The maximum likelihood method should preferably be used when compared to linearapproximation, ensuring a better quality in the prognoses of the diameter distribution.
The use of food additives and greenhouse gas (GHG) emissions are major factors that affect consumer health, which cannot be ensured, therefore, unless the food supply chain is controlled. This paper presents a bi-leve...
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The use of food additives and greenhouse gas (GHG) emissions are major factors that affect consumer health, which cannot be ensured, therefore, unless the food supply chain is controlled. This paper presents a bi-level optimization approach to address competition between the members of a food supply chain, including two suppliers and one manufacturer. The manufacturer seeks to determine prices, production, and investment in reducing GHG emissions to maximize profits at the upper level. A multi-period model is presented, in which the manufacturer seeks to reduce production costs by maintaining inventory and, of course, accepting the risk of waste. At the lower level, the suppliers compete to determine the price of raw materials and the amount of additives to maximize their profits. Two linear approximation methods are proposed to linearize the nonlinear model. According to the results, the lowest relative gaps obtained from solving the model for two numerical examples using the second linear approximation method are lower than those obtained by the first method. A sensitivity analysis of the effective parameters demonstrates that an increase in the dependence of demand on price leads to a 30% decrease in the profit of the entire supply chain. The manufacturer faces an average 3% drop in demand with an increase of 4%-7% in the rate of production waste. An 18% increase in the cost of GHG emission reduction leads to a 5% decrease in total supply chain profit. Hence, the increase in the cost of reducing GHG emissions is not economical and environment-friendly for the supply chain members. A budget increase is appropriate in terms of the economic and environmental goals, but its impact on the manufacturer's decision variables varies by period.
The inductive proximity sensor (IPS) is applicable to displacement measurements in the aviation field due to its non-mechanical contact, safety, and durability. IPS can increase reliability of position detection and d...
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The inductive proximity sensor (IPS) is applicable to displacement measurements in the aviation field due to its non-mechanical contact, safety, and durability. IPS can increase reliability of position detection and decrease maintenance cost of the system effectively in aircraft applications. Nevertheless, the specialty in the aviation field proposes many restrictions and requirements on the application of IPS, including the temperature drift effect of the resistance component of the IPS sensing coil. Moreover, reliability requirements of aircrafts restrict the use of computational-intensive algorithms and avoid the use of process control components. Furthermore, the environment of airborne electronic equipment restricts measurements driven by large current and proposes strict requirements on emission tests of radio frequency (RF) energy. For these reasons, a differential structured IPS measurement method is proposed in this paper. This measurement method inherits the numerical separation of the resistance and inductance components of the IPS sensing coil to improve the temperature adaptation of the IPS. The computational complexity is decreased by combining the dimension-reduced look-up table method to prevent the use of process control components. The proposed differential structured IPS is equipped with a differential structure of distant and nearby sensing coils to increase the detection accuracy. The small electric current pulse excitation decreases the RF energy emission. Verification results demonstrate that the differential structured IPS realizes the numerical decoupling calculation of the vector impedance of the sensing coil by using 61 look-up table units. The measuring sensitivity increased from 135.5 least significant bits (LSB)/0.10 mm of a single-sensing-coil structured IPS to 1201.4 LSB/0.10 mm, and the linearapproximation distance error decreased from 99.376 m to -3.240 m. The proposed differential structured IPS method has evident comparative adva
Inductive proximity sensors (IPSs) present a unique no-contact advantage. They are widely preferred for displacement measurement in various industrial fields (e.g., aviation and aerospace), and they are improved conti...
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Inductive proximity sensors (IPSs) present a unique no-contact advantage. They are widely preferred for displacement measurement in various industrial fields (e.g., aviation and aerospace), and they are improved continuously. When the inductance and resistance components of the IPS sensing core are separated, the influence of temperature drift on measurement can be eliminated. The complexity of online computation of component separation can be reduced using a two-dimensional look-up table method. However, this method exhibits disadvantages, such as large capacity of the look-up table, dependency on precision measurement of sensing core parameter, and nonlinear distribution of measurement resolution. This study aims to overcome these disadvantages by examining the nonlinear relationship between the response of the sensing core and the ambient temperature, and proposes a dimension-reduced measurement method. The proposed method extracts the characteristics of the response curves at two temperatures and calculates the characteristics of the response curves at any temperature using a linearapproximation. The look-up table capacity is less than 0.37% of the two-dimensional look-up table capacity (condensed) under the same condition;dimension reduction enables the construction of a complete look-up table directly by calibration procedures and avoids precise measurement on sensing core parameters;the calibration procedures establish uniform mapping of the distribution of measurement resolution. The experiment shows that, when the measurement ranges are 0-6, 0-5, and 0-4 mm, the maximum measurement errors are 0.140, 0.065, and 0.040 mm, respectively, under temperature ranging from 20 degrees C to 110 degrees C. This study extends the measurement range from 0-5 mm to 0-7 mm and improves the measurement accuracy over 0.1 mm (50% at 5 mm) compared with the two-dimensional look-up table method. Therefore, the proposed method not only inherits the advantages of the original met
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