ABSTRACT An efficient new method, based on the coupling between an enhanced simulated annealing a... more ABSTRACT An efficient new method, based on the coupling between an enhanced simulated annealing algorithm and the SPICE-PAC ‘open’ circuit simulator, is proposed for minimizing objective functions describing circuit performance optimization problems or component model fitting to experimental data. To keep the number of objective function evaluations and CPU times to the lowest possible level, we focus our attention on two features: first, we build an original partitioning technique for splitting large n-dimensional problems; then we carefully study variables discretization, (which is necessary for applying the simulated annealing method to continuous problems). To illustrate the efficiency of our method, we show how to determine the 40 MOS transistor model parameters, through fitting the model to experimental data.
A new global optimization algorithm for functions of many continuous variables is presented, deri... more A new global optimization algorithm for functions of many continuous variables is presented, derived from the basic Simulated Annealing method. Our main contribution lies in dealing with high-dimensionality minimization problems, which are often difficult to solve by all known ...
ABSTRACT Simulated annealing (SA) adapted to continuous variables is used lo determine the synapt... more ABSTRACT Simulated annealing (SA) adapted to continuous variables is used lo determine the synaptic coefficients of an analogue multilayer neural network, approximating any continuous function of one or several variables. The ‘open’ electrical simulator SPICE-PAC driven by SA produces a globally optimal set of synaptic weights, in a reasonable time and without requiring heavy and inaccurate gradient computations, We illustrate and improve our weights tuning strategy through simple examples.
In the paper, various parameters of a non-linear general purpose GaAs FET model are directly dete... more In the paper, various parameters of a non-linear general purpose GaAs FET model are directly determined by our Enhanced Simulated Annealing. We minimize an objective function of several continuous variables model parameters based on the relative and absolute least ...
Genetic algorithms are stochastic search approaches based on randomized operators, such as select... more Genetic algorithms are stochastic search approaches based on randomized operators, such as selection, crossover and mutation, inspired by the natural reproduction and evolution of the living creatures. However, few published works deal with their application to the global ...
ABSTRACT An efficient new method, based on the coupling between an enhanced simulated annealing a... more ABSTRACT An efficient new method, based on the coupling between an enhanced simulated annealing algorithm and the SPICE-PAC ‘open’ circuit simulator, is proposed for minimizing objective functions describing circuit performance optimization problems or component model fitting to experimental data. To keep the number of objective function evaluations and CPU times to the lowest possible level, we focus our attention on two features: first, we build an original partitioning technique for splitting large n-dimensional problems; then we carefully study variables discretization, (which is necessary for applying the simulated annealing method to continuous problems). To illustrate the efficiency of our method, we show how to determine the 40 MOS transistor model parameters, through fitting the model to experimental data.
A new global optimization algorithm for functions of many continuous variables is presented, deri... more A new global optimization algorithm for functions of many continuous variables is presented, derived from the basic Simulated Annealing method. Our main contribution lies in dealing with high-dimensionality minimization problems, which are often difficult to solve by all known ...
ABSTRACT Simulated annealing (SA) adapted to continuous variables is used lo determine the synapt... more ABSTRACT Simulated annealing (SA) adapted to continuous variables is used lo determine the synaptic coefficients of an analogue multilayer neural network, approximating any continuous function of one or several variables. The ‘open’ electrical simulator SPICE-PAC driven by SA produces a globally optimal set of synaptic weights, in a reasonable time and without requiring heavy and inaccurate gradient computations, We illustrate and improve our weights tuning strategy through simple examples.
In the paper, various parameters of a non-linear general purpose GaAs FET model are directly dete... more In the paper, various parameters of a non-linear general purpose GaAs FET model are directly determined by our Enhanced Simulated Annealing. We minimize an objective function of several continuous variables model parameters based on the relative and absolute least ...
Genetic algorithms are stochastic search approaches based on randomized operators, such as select... more Genetic algorithms are stochastic search approaches based on randomized operators, such as selection, crossover and mutation, inspired by the natural reproduction and evolution of the living creatures. However, few published works deal with their application to the global ...
Uploads