Now showing items 51-59 of 59
Myoelectric Teleoperation of a Complex Robotic Hand
Teleoperation continues to be a primary control mode in robotics applications, particularly for robots with complex hands. This paper details a novel method of teleoperation of complex anthropomorphic robotic hands: converting the myoelectric signal (generated by the operator's muscles during movement) into robot commands replicating the motion. ...
Optimal Kernels for Nonstationary Spectral Estimation
Current theories of a time-varying spectrum of a nonstationary process all involve, either by definition or by difficulties in estimation, an assumption that the signal statistics vary slowly over time. This restrictive quasi-stationarity assumption limits the use of existing estimation techniques to a small class of nonstationary processes. We ...
On Joint Distributions for Arbitrary Variables
There has been considerable interest in the problem of joint representations for variables other than time and frequency. In this letter we compare the methods of Cohen and of Baraniuk and Jones and show their equivalence for variables that have the same commutator as time and frequency. In addition we report the following very general result: all ...
Unitary Equivalence: A New Twist on Signal Processing
Unitary similarity transformations furnish a powerful vehicle for generating infinite generic classes of signal analysis and processing tools based on concepts different from time, frequency, and scale. Implementation of these new tools involves simply preprocessing the signal by a unitary transformation, performing standard processing techniques ...
A Signal-Dependent Time-Frequency Representation: Fast Algorithm for Optimal Kernel Design
A time-frequency representation based on an optimal, signal-dependent kernel has been proposed recetnly in an attempte to overcome one of the primary limitations of bilinear time-frequency distributions: that the best kernel and distribution depend on the signal to be analyzed. The optimization formulation for the signal-dependent kernel results ...
Beyond Time Frequency Analysis: Energy Densities in One and Many Dimensions
Given a unitary operator A representing a physical quantity of interest, we employ concepts from group representation theory to define two natural signal energy densities for A. The first is invariant to A and proves useful when the effect of A is to be ignored; the second is covariant to A and measures the "A" content of signals. The ...
A Pseudo-Bertrand Distribution for Time-Scale Analysis
Using the pseudo-Wigner time-frequency distribution as a guide, we derive two new time-scale representations, the pseudo-Bertrand and the smoothed pseudo-Bertrand distributions. Unlike the Bertrand distribution, these representations support efficient online operation at the same computational cost as the continuous wavelet transform. Moreover, ...
Signal Transform Covariant to Scale Changes
A unitary signal transformation that is covariant by translation to scale changes (dilations and compressions) in the signal is formulated and justified. Unlike the Mellin transform, which is invariant to scale changes, this new transform is a true indicator of the scale content of a signal.
Improved Time-Frequency Filtering of Signal-Averaged Electrocardiograms
A recently proposed time-frequency filtering technique has shown promising results for the enhancement of signal-averaged electrocardiograms. This method weights the short-time Fourier transform (STFT) of the ensemble-averaged signal, analogous to the spectral domain Wiener filtering of stationary signals. In effect, it is a self-designing time-varying ...