Abstract
This paper presents a nonlinear model based predictive controller (NMPC) for trajectory tracking of a mobile robot. Methods of numerical optimization to perform real time nonlinear minimization of the cost function are used. The cost function penalizes the robot position error, the robot orientation angle error and the control effort. Experimental results of the trajectories following and the performance of the methods of optimization are presented.

Abstract
We investigate the effects of diffusion on the evolution of steady-state dark and gray spatial solitons in biased photorefractive media. Numerical integration of the nonlinear propagation equation shows that the soliton beams experience a modification of their initial trajectory, as well as a variation of their minimum intensity. This process is further studied using perturbation analysis, which predicts that the center of the optical beam moves along a parabolic trajectory and, moreover, that its minimum intensity varies linearly with the propagation distance, either increasing or decreasing depending on the sign of the initial transverse velocity. Relevant examples are provided.

Abstract
We present a new group of audio effects that use beat tracking, the detection of beats in an audio signal, to relate effect parameters to the beats in an input signal. Conventional audio effects are augmented so that their operation is related to the output of a beat tracking system. We present a temposynchronous delay effect and a set of beat synchronous low frequency oscillator effects including tremolo, vibrato and auto-wah. All effects are implemented in real-time as VST plug-ins to allow for their use in live performance.

Abstract
We present a simple and efficient method for beat tracking of musical audio. With the aim of replicating the human ability of tapping in time to music, we formulate our approach using a two state model. The first state performs tempo induction and tracks tempo changes, while the second maintains contextual continuity within a single tempo hypothesis. Beat times are recovered by passing the output of an onset detection function through adaptively weighted comb filterbank matrices to separately identify the beat period and alignment. We evaluate our beat tracker both in terms of the accuracy of estimated beat locations and computational complexity. In a direct comparison with existing algorithms, we demonstrate equivalent performance at significantly reduced computational cost.

Abstract
Despite continued attention toward the problem of automatic beat detection in musical audio, the issue of how to evaluate beat tracking systems remains pertinent and controversial. As yet no consistent evaluation metric has been adopted by the research community. To this aim, we propose a new method for beat tracking evaluation by measuring beat accuracy in terms of the entropy of a beat error histogram. We demonstrate the ability of our approach to address several shortcomings of existing methods.

Abstract
This is an extended analysis of eight different algorithms for musical tempo extraction and beat tracking. The algorithms participated in the 2006 Music Information Retrieval Evaluation eXchange (MIREX), where they were evaluated using a set of 140 musical excerpts, each with beats annotated by 40 different listeners. Performance metrics were constructed to measure the algorithms' abilities to predict the most perceptually salient musical beats and tempi of the excerpts. Detailed results of the evaluation are presented here and algorithm performance is evaluated as a function of musical genre, the presence of percussion, musical meter and the most salient perceptual tempo of each excerpt.