Parametric Encoding of Haptic-Tactile Signals Using Chebyshev Polynomials
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies face challenges in efficiently encoding and transporting haptic-tactile signals at low bit rates, making it difficult to deliver these signals effectively from production to consumption, especially in real-time applications like broadcasting.
Innovation Solution
The use of low bit rate parametric encoding techniques, such as functional representations based on Chebyshev polynomials or polynomial approximations, to represent haptic-tactile signals, allowing for efficient coding and decoding while maintaining a good waveform match, and the integration of these parameters into compressed audio bit streams for transport.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional encoding methods are used for haptic-tactile signals, then signal fidelity is maintained, but bit rate becomes excessively high for efficient transport and real-time broadcasting
Solution Approach 1:
The patent transforms the haptic-tactile signal from time-domain representation to frequency-domain representation using Fourier transform. This parameter transformation allows the signal to be encoded using spectral parameters (amplitude and phase spectra) rather than raw time-series data, achieving significant bit rate reduction while preserving signal fidelity through selective parameter transmission
Solution Approach 2:
The patent extracts only the essential parameters needed to reconstruct the haptic signal - specifically the amplitude spectrum and phase spectrum obtained through Fourier transform. By separating and transmitting only these critical parameters rather than the complete signal, the method achieves efficient compression while maintaining reconstruction quality
2Productivity
If compression is applied to reduce bit rate, then transport efficiency improves, but waveform match between source and decoded signals deteriorates
Solution Approach 1:
The patent performs Fourier transform and parameter extraction before compression and transport. By pre-processing the signal to extract amplitude and phase spectra, the system prepares the data in a form that can be efficiently compressed and later reconstructed, ensuring waveform fidelity is maintained despite compression
Solution Approach 2:
The patent replaces direct time-domain signal transmission with frequency-domain parameter transmission. This substitution allows the signal to be represented and reconstructed using mathematical parameters (spectral components) rather than mechanical sample-by-sample transmission, achieving both compression and fidelity
3Manufacturing precision
If complex encoding algorithms are used to maintain signal quality, then waveform match improves, but processing complexity and computational requirements increase
Solution Approach 1:
The patent segments the haptic signal processing into distinct stages: Fourier transform for spectral analysis, separate amplitude and phase extraction, independent compression of each spectral component, and ordered reconstruction. This segmentation allows each stage to be optimized independently, reducing overall processing complexity while maintaining waveform fidelity
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Techniques for low bit rate parametric encoding of haptic-tactile signals. The techniques encompass a parametric encoding method. The parametric encoding method includes the steps of: for at least one frame of a plurality of frames of a source haptic-tactile signal, representing the source haptic-tactile signal in the frame as a set of parameters and according to a functional representation; and including the set of parameters in a bit stream that encodes the source haptic-tactile signal. The functional representation is based on one of a set of orthogonal functionals, or polynomial approximation. For example, the functional representation can be based on one of Chebyshev functionals of the first kind through order n, Chebyshev functionals of the second kind through order n, or k-th order polynomial approximation.