Hrirs' Adaptive Non-Linear Approximation Model Based on Wavelet Transformation
During the study of spatial hearing, it is requisite to consider how to properly model the acoustical characteristics of HRTFs (head-related transfer functions: HRTFs) or HRIRs (head-related impulse responses: HRIRs) corresponding to certain positions. In our work, we managed to carry through adaptive non-linear approximation in the field of wavelet transformation. The results show that, the HRIRs' adaptive nonlinear approximation model is a more effective data reduction model, faster and averagely 5 dB better than the traditional PCA (Karhunen-Loeve transform) model based on relative error
Knowledge of the heat transfer coefficient is believed to be of great contribution in the course of a full design of a solar dryer. To find an expression for the heat transfer coefficient, the general logarithmic velocity profile for turbulent flow is used for the analysis. It is assumed that the fluid is air at atmospheric pressure, and that the thin wall laminar sublayer has a small or negligible effect on the value of the fluid bulk temperature. The final form of the correlation equation gives a relation between Nusselt number and Reynolds’ number, and is given in a form which is easy to remember by the solar dryer designers. Comparison of the predicted values indicates that the correlation can predict values to within  6% of experimental values reported in literature. Expected errors of nearly  25% were observed when the correlation predictions compared with well