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1.
Journal of Medical Biomechanics ; (6): 414-417, 2009.
Article in Chinese | WPRIM | ID: wpr-737270

ABSTRACT

Objective To study the method of internal boundary parameters identification of middle ear.Method The numerical model is created using CT technology.Based on Matlab tools,the neural network for identifying internal boundary is proposed.Result The uniform pressure of 105 dB is applied at the outside of the tympanic membrane,and the harmonic analysis is calculated on the model to take the training samples.The internal condition parameters are identified using the good neural network.Conclusions The investiga-tion shows that the inverse method reveals a fast convergence and a high degree of accuracy.

2.
Journal of Medical Biomechanics ; (6): 414-417, 2009.
Article in Chinese | WPRIM | ID: wpr-735802

ABSTRACT

Objective To study the method of internal boundary parameters identification of middle ear.Method The numerical model is created using CT technology.Based on Matlab tools,the neural network for identifying internal boundary is proposed.Result The uniform pressure of 105 dB is applied at the outside of the tympanic membrane,and the harmonic analysis is calculated on the model to take the training samples.The internal condition parameters are identified using the good neural network.Conclusions The investiga-tion shows that the inverse method reveals a fast convergence and a high degree of accuracy.

3.
Journal of Medical Biomechanics ; (6): 414-417, 2009.
Article in Chinese | WPRIM | ID: wpr-472360

ABSTRACT

Objective To study the method of internal boundary parameters identification of middle ear.Method The numerical model is created using CT technology.Based on Matlab tools,the neural network for identifying internal boundary is proposed.Result The uniform pressure of 105 dB is applied at the outside of the tympanic membrane,and the harmonic analysis is calculated on the model to take the training samples.The internal condition parameters are identified using the good neural network.Conclusions The investiga-tion shows that the inverse method reveals a fast convergence and a high degree of accuracy.

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