In order to alleviate the shortcomings of most blind deconvolution algorithms,this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix.Althougt...In order to alleviate the shortcomings of most blind deconvolution algorithms,this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix.Althougth the original algorithm can overcome the shortcomings of current blind deconvolution algorithms,it has a constraint that the number of the source signals must be less than that of the channels.The improved algorithm deletes this constraint by using decorrelation technique.Besides,the improved algorithm raises the separation speed in terms of improving the computing methods of the output signal matrix.Simulation results demonstrate the validation and fast separation of the improved algorithm.展开更多
The present paper describes an optimization work to obtain the properties related to a pyrolysis process in the solid material such as density, specific heat, conductivity of virgin and char, heat of pyrolysis and kin...The present paper describes an optimization work to obtain the properties related to a pyrolysis process in the solid material such as density, specific heat, conductivity of virgin and char, heat of pyrolysis and kinetic parameters used for deciding pyrolysis rate. A repulsive particle swarm optimization algorithm is used to obtain the pyrolysis-related properties. In the previous study all properties obtained only using a cone calorimeter but in this paper both the cone calorimeter and thermo gravimetric analysis (TGA) are used for precisely optimizing the pyrolysis properties. In the TGA test a very small mass is heated up and conduction and heat capacity in the specimen is negligible so kinetic parameters can first be optimized. Other pyrolysis-related properties such as virgin/char specific heat and conductivity and char density are also optimized in the cone calorimeter test with the already decided parameters in the TGA test.展开更多
基金Natural Science Fund of Anhui Province of China (050420101)
文摘In order to alleviate the shortcomings of most blind deconvolution algorithms,this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix.Althougth the original algorithm can overcome the shortcomings of current blind deconvolution algorithms,it has a constraint that the number of the source signals must be less than that of the channels.The improved algorithm deletes this constraint by using decorrelation technique.Besides,the improved algorithm raises the separation speed in terms of improving the computing methods of the output signal matrix.Simulation results demonstrate the validation and fast separation of the improved algorithm.
文摘The present paper describes an optimization work to obtain the properties related to a pyrolysis process in the solid material such as density, specific heat, conductivity of virgin and char, heat of pyrolysis and kinetic parameters used for deciding pyrolysis rate. A repulsive particle swarm optimization algorithm is used to obtain the pyrolysis-related properties. In the previous study all properties obtained only using a cone calorimeter but in this paper both the cone calorimeter and thermo gravimetric analysis (TGA) are used for precisely optimizing the pyrolysis properties. In the TGA test a very small mass is heated up and conduction and heat capacity in the specimen is negligible so kinetic parameters can first be optimized. Other pyrolysis-related properties such as virgin/char specific heat and conductivity and char density are also optimized in the cone calorimeter test with the already decided parameters in the TGA test.
