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Document clustering groups documents of certain similar characteristics in one cluster. Document clustering has shown advantages on organization, retrieval, navigation and summarization of a huge amount of text documents on Internet. This paper presents a novel, unsupervised approach for clustering single-author documents into groups based on authorship. The key novelty is that we propose to extract...
Fast and accurate measuring depth of anesthesia (DoA) during heavy surgeries (e.g. orthopedic or neurosurgery) is still a challenge. Late estimation of DoA in critical conditions may lead to severe effects such as a comma or conscious state, and jeopardize patient's life accordingly. Recently, several attempts have been made to elicit an accurate DoA index by analyzing electroencephalogram (EEG) signals,...
In this paper, we investigate the recovery of range and spectral profiles associated with remote three-dimensional scenes sensed via single-photon multispectral Lidar (MSL). We consider different spatial/spectral sampling strategies and pare their performance for similar overall numbers of detected photons. For a regular spatial grid, the first strategy consists of sampling all the spatial locations...
This paper presents a new adaptation of Zadoff-Chu sequences for the purpose of range estimation and movement tracking. The proposed method uses Zadoff-Chu sequences utilizing a wideband ultrasonic signal to estimate the range between two devices with very high accuracy and high update rate. This range estimation method is based on time of flight (TOF) estimation using cyclic cross correlation. The...
Currently the number of applications where the data generation function is not known has been growing, making necessary the use of non-parametric estimation techniques to describe such model. Therefore, relevant questions emerge regarding the quality of the model that represents some dataset and how to quantify this quality. This article aims to evaluate some of the measurements presented in the literature...
It is indispensable to take a low complexity and high accuracy channel estimation algorithm into account under rapidly growth in wireless communication. In this paper, we propose an algorithm for channel estimation using complementary sequence (CS). By utilizing the fantastic autocorrelation property of CS, time domain channel estimation can be easily achieved. We analyzed the complementary sequence,...
Co-prime arrays have gained in popularity as an efficient way to estimate second order statistics at the Nyquist rate from sub-Nyquist samples without any sparsity constraint. We derive an expression for the degrees of freedom and the number of consecutive values in the difference set for the prototype co-prime array. This work shows that, under the wide sense stationarity (WSS) condition, larger...
This paper studies the estimation of the desired signal received on the array antenna in the correlated wireless communication environment. The direction of arrival signal applies updated weight to the Bartlett method for estimation the desired signals. In this paper, the proposed method applies the optimal weight vector to the output energy of the Bartlett method. Through simulation, we compare proposed...
Tracheoesophageal (TE) speech is generated by patients who have undergone a total laryngectomy where the larynx (voice box) is removed and replaced by a tracheoesophageal puncture. This work presents a novel low complexity algorithm to estimate the degree of severity of disordered TE speech. The proposed algorithm uses features which are computed from 32-ms voiced frames of the speech signal. A 21-st...
In this paper, we present an impression estimation method for television commercials with a visualization method. Our method estimates the impressions viewers might have of a new proposal for a TV commercial written in text as weighted favorable factors and visualizes the estimated favorable factors. During the production of TV commercials, it is important to create commercials that clearly communicate...
The downlink positioning method specified by 3GPP is a part of LTE location service. The method utilizes the time difference of Positioning Reference Signal (PRS) for ranging, therefore time delay estimation of PRS is a fundamental question in the method. A conventional algorithm relies on time correlation however faces challenges in multipath channel. For OFDM signal, Multiple Signal Classification...
Because of the phenomenon that various support equipment reduce the security system deployment and economy, this paper analyzed the cost and efficiency of intensive security equipment that made by some similar function equipment. The measurement costs were taken into account in the cost model. To sort out the parameter values of the initial support devices, make them dimensionless, and select parameters...
The notion of complexity is widely-known and used. Various definitions of complexity exist: the Hausdorff dimension, fractal dimension, Kolmogorov complexity, Krohn-Rhodes complexity, Lyapunov exponents or the entropy, some of them with several definitions. All these measures were defined strictly for mathematical objects, but they may apply to real signals like texture images in particular. We are...
In view of the traditional correlation integral optimization method, when the system disturbances are correlative with the decision variables, objective function does not converge to the optimal value in the process of iterative optimization. In this work, an improved method of correlation integral optimization is proposed. Based on the steady data driven model, an adaptive disturbance estimator is...
We address the problem of determining correspondences between two images in agreement with a geometric model such as an affine or thin-plate spline transformation, and estimating its parameters. The contributions of this work are three-fold. First, we propose a convolutional neural network architecture for geometric matching. The architecture is based on three main components that mimic the standard...
Sparse unmixing of hyperspectral data is an important technique which aims at estimating the fractional abundances of endmembers (pure spectral components). It is well known that enforcing sparseness becomes a necessary process in sparse unmixing methods. To better exploit the sparsity in hyperspectral imagery, a double reweighted sparse unmixing algorithm has been proposed. However, it focusses on...
In this paper, we propose a multiple line extraction method from multimodal data points in high dimensional space. It can sparsely represent multimodal sensor network data by utilizing high correlation among channels in the data. We exploit the idea of Color Lines, which is a model using high correlation among RGB channels in computer vision. It represents real color images as a collection of multiple...
This work is focused on the task of multimodal saliency detection. Very few works have been developed in the field, and there are no well-established baselines or benchmarks comparable to those existing in the field of visual saliency detection. In this paper, we set out to improve an existing model by enhancing the performance of its key module: the audio-visual correlation estimation based on the...
High resolution sea ice drift fields, the location and extend of converging and diverging zones as well as ice ridges are most important parameters for ship navigation in ice infested waters. In this paper, we present the prototype of a new processor which is aimed to derive the surface ice parameters on the basis of pairs of space-borne Synthetic Aperture Radar (SAR) data of the same and of different...
the task of full-focused digital images construction relates to computational photography and is a process of increasing the information capacity of images obtained via photo- and video-fixation devices with limited optical depth of field. Additional to this task is the question of automatic evaluation of the quality of the images. The most popular non-reference metrics for comparing the quality of...
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