A High Power, High Efficiency, Isotopically CO2 Optically Pumped, 15NH3 Far-Infrared (FIR) Laser System

1981 ◽  
Author(s):  
B. Norris ◽  
M. J. CoIles ◽  
R. A. Wood ◽  
A. Vass ◽  
C. R. Pidgeon
Keyword(s):  
High Power ◽  
High Efficiency ◽  
Laser System ◽  
Far Infrared ◽  
Fir Laser ◽  
Optically Pumped

High power, high efficiency optically pumped NH3 lasers

1990 ◽  
Vol 51 (5) ◽  
pp. 371-373 ◽  
Author(s):  
J. D. White ◽  
A. Chakrabarti ◽  
J. Reid
Keyword(s):  
High Power ◽  
High Efficiency ◽  
Optically Pumped

MODELLING AND PREDICTION FOR CHAOTIC FIR LASER ATTRACTOR USING RATIONAL FUNCTION NEURAL NETWORK

2001 ◽  
Vol 11 (01) ◽  
pp. 89-99 ◽  
Author(s):  
Seongyun Cho
Keyword(s):  
Neural Network ◽  
Rational Function ◽  
Radial Basis Function Network ◽  
Laser System ◽  
Far Infrared ◽  
Network Architectures ◽  
Fir Laser ◽  
Currency Exchange ◽  
Currency Exchange Rate ◽  
Function Network

Many real-world systems such as irregular ECG signal, volatility of currency exchange rate and heated fluid reaction exhibit higly complex nonlinear characteristic known as chaos. These chaotic systems cannot be retreated satisfactorily using linear system theory due to its high dimensionality and irregularity. This research focuses on prediction and modelling of chaotic FIR (Far InfraRed) laser system for which the underlying equations are not given. This paper proposed a method for prediction and modelling a chaotic FIR laser time series using rational function neural network. Three network architectures, TDNN (Time Delayed Neural Network), RBF (radial basis function) network and the RF (rational function) network, are also presented. Comparisons between these networks performance show the improvements introduced by the RF network in terms of a decrement in network complexity and better ability of predictability.

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