The basic objective of time-scale transformation is to compress or expand the signal in time field while keeping the same spectral properties. This paper presents two methods to derive time-scale transformation formul...The basic objective of time-scale transformation is to compress or expand the signal in time field while keeping the same spectral properties. This paper presents two methods to derive time-scale transformation formula based on continuous wavelet transform. For an arbitrary given square-integrable function f(t),g(t) = f(t/λ) is derived by continuous wavelet transform and its inverse transform. The result shows that time-scale transformation may be obtained through the modification of the time-scale of wavelet function filter using equivalent substitution. The paper demonstrates the result by theoretic derivations and experimental simulation.展开更多
Wavelet has been used as a powerful tool in the signal processing and function approximation recently. This paper presents the application of wavelets for solving two key problems in 3-D audio simulation. First, we em...Wavelet has been used as a powerful tool in the signal processing and function approximation recently. This paper presents the application of wavelets for solving two key problems in 3-D audio simulation. First, we employ discrete wavelet transform (DWT) combined with vector quantization (VQ) to compress audio data in order to reduce tremendous redundant data storage and transmission times. Secondly, we use wavelets as the activation functions in neural networks called feed-forward wavelet networks to approach auditory localization information cues (head-related transfer functions (HRTFs) are used here). The experimental results demonstrate that the application of wavelets is more efficient and useful in 3-D audio simulation.展开更多
文摘The basic objective of time-scale transformation is to compress or expand the signal in time field while keeping the same spectral properties. This paper presents two methods to derive time-scale transformation formula based on continuous wavelet transform. For an arbitrary given square-integrable function f(t),g(t) = f(t/λ) is derived by continuous wavelet transform and its inverse transform. The result shows that time-scale transformation may be obtained through the modification of the time-scale of wavelet function filter using equivalent substitution. The paper demonstrates the result by theoretic derivations and experimental simulation.
文摘Wavelet has been used as a powerful tool in the signal processing and function approximation recently. This paper presents the application of wavelets for solving two key problems in 3-D audio simulation. First, we employ discrete wavelet transform (DWT) combined with vector quantization (VQ) to compress audio data in order to reduce tremendous redundant data storage and transmission times. Secondly, we use wavelets as the activation functions in neural networks called feed-forward wavelet networks to approach auditory localization information cues (head-related transfer functions (HRTFs) are used here). The experimental results demonstrate that the application of wavelets is more efficient and useful in 3-D audio simulation.
