Efficient model fitting using a genetic algorithm pole-zero approximations of HRTFs.

We demonstrate that a genetic algorithm (GA) can efficiently generate accurate low-order pole-zero approximations of head-related transfer functions (HRTFs) from measured impulse responses by minimizing a logarithmic error criterion. This approach is much simpler and comparable or superior in effici...

תיאור מלא

מידע ביבליוגרפי
הוצא לאור ב:	IEEE Transactions on speech and audio processing 10, 1 (2002).
מחבר ראשי:	Durant, E.A
פורמט:	Article
שפה:	English
נושאים:	Convergence detection. Discrete-time pole-zero filter design. Domain-appropriate error measure. Efficient model fitting. Genetic algorithm. Head-related transfer functions. Logarithmic error criterion. Low-order HRTF approximation. Lower bound. Measured impulse responses. Performance measurements. Pole-zero approximations. Population variation metric. Search algorithms. Steady-state GA.