Piecewise Linear Slope Estimation.

This paper presents a method for directly estimating slope values in a noisy piecewise linear function. By imposing a Markov structure on the sequence of slopes, piecewise linear fitting is posed as a maximum a posteriori estimation problem. A dynamic program efficiently solves this by traversing a linearly growing trellis. The alternating maximization algorithm (a kind of pseudo-EM method) is used to estimate the model parameters from data and its convergence behavior is analyzed. Ultrasound shear wave imaging is presented as a primary application. The algorithm is general enough for applicability in other fields, as suggested by an application to the estimation of shifts in financial interest rate data.

The least-squares invertible constant-Q spectrogram and its application to phase vocoding.

This paper discusses the development of a constant-Q spectrogram representation that is invertible in a least-squares sense. A good quality inverse is possible because this modified transform method, unlike the usual sliding window constant-Q spectrogram, does not discard data samples when performing the variable length discrete Fourier transforms on the signal. The development of a phase vocoder application using this modified technique is also discussed. It is shown that a phase vocoder constructed using the least-squares invertible constant-Q spectrogram (LSICQS) is not a trivial extension of the regular FFT-based phase vocoder algorithm and some of the mathematical subtleties related to phase reassignment are addressed.