A real-time optimal filtering algorithm for stochastic systems with multiresolutional measurements is derived. The algorithm gives fused estimates based upon all available data at a particular time index. A multiresol...
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A real-time optimal filtering algorithm for stochastic systems with multiresolutional measurements is derived. The algorithm gives fused estimates based upon all available data at a particular time index. A multiresolutional distributed filtering scheme is employed. The wavelet transform is utilized as a bridge, effectively linking different resolution levels. A tree-like hierarchical data structure introduced in this paper facilitates the real-time multiresolutional filtering.
The purpose of this paper is to present wavelet-based noise removal (WBNR) techniques to remove noise from biomechanical acceleration signals obtained from numerical differentiation of displacement data. Manual and se...
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The purpose of this paper is to present wavelet-based noise removal (WBNR) techniques to remove noise from biomechanical acceleration signals obtained from numerical differentiation of displacement data. Manual and semiautomatic methods were used to determine thresholds for both orthogonal and biorthogonal filters. This study also compares the performance of WBNR approaches with four automatic conventional noise removal techniques used in biomechanics, The conclusion of this work is that WBNR techniques are very effective in removing noise from differentiated signals with sharp transients while leaving these transients intact. For biomechanical signals with certain characteristics, WBNR techniques perform better than conventional methods, as indicated by quantitative merit measures.
In 1983, Burt and Adelson introduced the Laplacian pyramid (LP) as a multiresolution representation for images. We study the LP using the frame theory, and this reveals that the usual reconstruction is suboptimal. We ...
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In 1983, Burt and Adelson introduced the Laplacian pyramid (LP) as a multiresolution representation for images. We study the LP using the frame theory, and this reveals that the usual reconstruction is suboptimal. We show that the LP with orthogonal filters is a tight frame, and thus, the optimal linear reconstruction using the dual frame operator has a simple structure that is symmetric, with the forward transform. In more general cases, we propose an efficient filterbank (FB) for the reconstruction of the LP using projection that leads to a proved improvement over the usual method in the presence of noise. Setting up the LP as an oversampled FB, we offer a complete parameterization of all synthesis FBs that provide perfect reconstruction for the LP. Finally, we consider the situation where the LP scheme is iterated and derive the continuous-domain frames associated with the LP.
Astronomical imaging of a star cluster is one of the paramount ways to learn about stellar evolution, stellar dynamics. A large telescope is not generally accessible to all observers. In that context, small telescope ...
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Astronomical imaging of a star cluster is one of the paramount ways to learn about stellar evolution, stellar dynamics. A large telescope is not generally accessible to all observers. In that context, small telescope observations with a proper denoising scheme can be an excellent alternative. This paper proposes a technique to denoise star cluster data using an undecimated wavelet transform, with a modified thresholding process. Our work aims to prove the effectiveness of such a wavelet-based technique on real-time data. We present drastically noise-infested observational data of the NGC 2301 star cluster, captured over five nights from Fr. Eugene Lafont Observatory, Kolkata. We observe that for highly noise-polluted data, the conventional methods of dark frame subtraction and flat frame division are inadequate to produce the desired quality of images due to functioning exclusively in the spatial domain. Thus, we take the wavelet-based multiresolution approach to ameliorate those raw images. We also introduce a modified thresholding function to modulate the image at different resolution levels. A standard star detecting software Daophot II quantifies the increment in the number of detected stars from raw images to the images processed by our proposed method as: for red filter 397-903, for green filter 663-945, for blue filter 362-896. On the contrary, Daophot II can't detect any star in the highly noise-polluted images processed by the conventional methods. Therefore, we hope our proposed processing methodology will motivate others to initiate small telescope observations from any site restrained by its geographical location.
State of the art vocabulary-independent spoken term detection methods are typically based on variants of the dynamic time warping (DTW) algorithm since DTW, being based on acoustic sequence matching, allows robust ret...
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State of the art vocabulary-independent spoken term detection methods are typically based on variants of the dynamic time warping (DTW) algorithm since DTW, being based on acoustic sequence matching, allows robust retrieval in settings with scarcity of linguistic resources. However, the DTW comes with a high computational cost which limits its practicality in a deployed server. To this end, we investigate the efficacy of subsampling and propose a neural network architecture to reduce the computational load of DTW-based keyword search. We use a time-subsampled RNN to reduce the frame rate of the document as well as the dimensionality of representation while training it to maintain the cost incurred along the DTW alignment path, thus allowing us to reduce the computational complexity (both space and time) of the search algorithm. Experiments on the Turkish and Zulu limited language packs of the IARPA Babel program show that the proposed methods allow considerable reduction in CPU time (88 times) and memory usage (18 times) without significant loss in search accuracy (0.0270 ATWV). Moreover, even at very high compression levels with lower search precision, high recall rates are maintained, allowing the potential of multi-resolution search.
This paper describes our work toward the development of a computationally robust methodology to identify the pyloric neurons in the stomatogastric ganglion of Cancer pagurus using voltage-sensitive dye imaging. The mu...
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ISBN:
(纸本)9781509039821
This paper describes our work toward the development of a computationally robust methodology to identify the pyloric neurons in the stomatogastric ganglion of Cancer pagurus using voltage-sensitive dye imaging. The multi-resolution signal decomposition procedure constructed using the sequential Singular Spectrum Analysis approach to isolate the pyloric rhythm from optical recordings of dyed live cells is presented. Early results suggest that the developed procedure offers a demonstrably reliable way to extract the rhythm from the recording data of these cells.
The combination of intra and extra-cellular recording of small neuronal circuits such as stomatogastric nervous systems of the crab (Cancer borealis) is well documented and routinely practised. Voltage sensitive dye i...
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ISBN:
(纸本)9781538604465
The combination of intra and extra-cellular recording of small neuronal circuits such as stomatogastric nervous systems of the crab (Cancer borealis) is well documented and routinely practised. Voltage sensitive dye imaging (VSDi) is a promising technology for the simultaneous monitoring of neuronal activities in such a system. However, integrating data obtained from optical VSDi and electrophysiological recording of the lateral ventricular nerve (lvn) is a complex and exacting task. Our early work demonstrated some of the concepts and principle involved. In this paper, we examine and report on the results obtained from the application of signalprocessing techniques to three datasets for which we had VSDi and lvn data. Whilst significant challenges remain, we show that such an approach offers the possibility of real-time monitoring using automated analysis of VSDi data streams without the requirement for either extracellular (lvn) or intracellular recording.
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