We consider the problem of segmenting an audio signal into characteristic regions based on feature-set similarities. In the proposed method, a feature-space representation of the signal is generated; then, sequences of feature-space samples are aggregated into clusters corresponding to distinct signal regions. The clustering of feature sets is improved via linear discriminant analysis (LDA); dy...

This paper presents a probabilistic framework for short-term (within a limited planning horizon) passive cooperation among unmanned aerial vehicles (UAV’s) performing a search. This structure is suitable for solution using a Dynamic Programming (DP) planning algorithm. Because of the exponential computational complexity of the DP algorithm, an ideal cooperation scheme is not feasible for implem...

Approximate searching on protein sequence data under arbitrary cost models is not supported by database indexing technology. We present a new data structure, suffix sequoia, which reduces the time complexity of the dynamic programming (DP) matrix calculation required in approximate matching. The data structure is compact. It uses just over 4 Bytes per symbol indexed. We show that time complexit...

We study the fixed design segmented regression problem – a classical statistical inference task that encompasses several natural problems as a special case. Given noisy samples from a piecewise linear function f , we want to recover f up to a desired accuracy in mean-squared error. Previous rigorous approaches for this problem rely on dynamic programming (DP) and, while sample efficient, have r...

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the pos...

In this paper, traditional process design rules for deep drawing of box shapes are used to develop constraints within a dynamic programming (DP) approach to generate a set of alternative optimized process plans that minimize the number of drawing stages and heat treatments. The DP approach is capable of scanning a wide range of different alternative values for process parameters which allows fo...

This article proposes a novel road extraction methodology from digital images. The innovation is based on the dynamic programming (DP) algorithm to carry out the optimisation process in the object space, instead of doing it in the image space such as the DP traditional methodologies. Road features are traced in the object space, which implies that a rigorous mathematical model is necessary to b...

Recent randomized asymptotically optimal motion planners incrementally construct an approximate, discrete, sparse representation of the underlying continuous search space, and use locally optimal solutions, along with a local reassignment of the edges, to obtain optimal solutions encoded in the current graph/tree data structure. Careful analysis reveals that all these algorithms can be interpre...

In this paper we propose a 3D expansion of DP (dynamic programming) to find a near optimal surface in a 3D matrix. This algorithm can detect boundaries in an image sequence such as B-mode sonographic images and MRI sequences. We test this algorithm using real B-mode CCA (common carotid artery) dynamic sonographic image sequences and FA (femoral artery) MRI sequences. The automated results are c...