This paper studies the addition of linear constraints to Support Vector Regression when kernel is linear. Adding those into problem allows add prior knowledge on estimator obtained, such as finding positive vector, probability vector or monotone data. We prove that related optimization stays a semi-definite quadratic problem. also propose generalization Sequential Minimal Optimization algorithm...

Examining articulatory compensation has been important in understanding how the speech production system is organized, and how it relates to the acoustic and ultimately phonological levels. This paper offers a method that detects articulatory compensation in the acoustic signal, which is based on linear regression modeling of co-variation patterns between acoustic cues. We demonstrate the metho...

Studies on iterative identification and model based control design have shown the necessity for identifying models on the basis of closed-loop data. Estimating models on the basis of closed-loop data requires special attention due to cross correlation of noise and input signals and the possibility to estimate unstable systems operating under a stabilizing closed-loop controller. This paper prov...