The major results of this work are: 1. we introduce the concepts of composite vs. basic symbols and composite vs. basic states and define a generalized EMM to allow variable length and depth of dependency;2. we define...
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Line following robots are used in numerous application areas. The tracking of weak line is challenging, especially if SNR is high, so application of Track-Before-Detect algorithm is necessary. The viterbi algorithm is...
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ISBN:
(纸本)9783319238142;9783319238135
Line following robots are used in numerous application areas. The tracking of weak line is challenging, especially if SNR is high, so application of Track-Before-Detect algorithm is necessary. The viterbi algorithm is assumed in this paper and the possibilities of optimization are considered. Two metric are applied in Monte Carlo tests-the direct metric and proposed boundary metric. The optimization of viterbi algorithm is based on non single row movements of moving window.
The text line segmentation process is a key step in an optical character recognition (OCR) system. Several common approaches, such as projection-based methods and stochastic methods, have been put forward to fulfill t...
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ISBN:
(纸本)9781509006540
The text line segmentation process is a key step in an optical character recognition (OCR) system. Several common approaches, such as projection-based methods and stochastic methods, have been put forward to fulfill this task. However, most of existing methods cannot be directly applied to process the palm leaf manuscripts of Dai which the images have poor quality and include smudges, creases, stroke deformation and character touching. To solve this problem, an improved viterbi algorithm based on Hidden Markov Model (HMM) is proposed to find all possible segmentation paths firstly. And then, a path filtering method is used to detect the optimal paths for the segmented text blocks. The performance of the method is compared with relevant methods and the experimental results demonstrate the effectiveness of the proposed method.
In this work a real-time indoor localisation system based on the viterbi algorithm is developed. This viterbi principle is used in combination with semantic data to improve the accuracy: i.e., the environment of the o...
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ISBN:
(纸本)9788890701856
In this work a real-time indoor localisation system based on the viterbi algorithm is developed. This viterbi principle is used in combination with semantic data to improve the accuracy: i.e., the environment of the object that is being tracked and an adjustable maximum speed. The developed algorithm was verified by simulations and with experiments in a building-wide testbed for sensor and WiFi experiments. Compared to a reference algorithm without viterbi or semantic data, the results indicated a significant improvement: the mean accuracy and standard deviation improved by respectively 26.4% and 63.9%.
Advances in microscope hardware in the last couple of decades have made it possible to acquire large data sets with image sequences of living cells grown in cell culture. This has led to a demand for automated ways of...
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ISBN:
(纸本)9781457718588
Advances in microscope hardware in the last couple of decades have made it possible to acquire large data sets with image sequences of living cells grown in cell culture. This has led to a demand for automated ways of analyzing the acquired images. This article presents a new algorithm for tracking cells and constructing cell lineages in such image sequences. The algorithm uses information from the entire sequence to make local decisions about cell tracks and can therefore make more robust decisions than algorithms that process the data sequentially. It also incorporates image-based likelihoods of cell division and cell death into the tracking, without having to resort to separate detection algorithms or post processing of tracks. The algorithm consists of a scoring function to rank tracks and an iterative algorithm that searches for the highest scoring tracks, in a computationally efficient way, using the viterbi algorithm.
Optimum receiver model for channels with Intersymbol Interference (ISI) and Additive White Gaussian Noise (AWGN) are introduced to deduce the viterbi algorithm in the Maximum-Likelihood Sequence Estimation (MLSE). Fin...
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ISBN:
(纸本)9783037854969
Optimum receiver model for channels with Intersymbol Interference (ISI) and Additive White Gaussian Noise (AWGN) are introduced to deduce the viterbi algorithm in the Maximum-Likelihood Sequence Estimation (MLSE). Finally, we use Matlab to simulate the algorithm in three different channels and analyze the experiment results. Analyses show that the viterbi algorithm is applicable for any channel which is optimum from a probability of error viewpoint;the MLSE for channels with ISI has a computational complexity that grows exponentially with the length of channels time dispersion L;the loss of performance is negligible when the decoding delay achieves 5L.
This paper describes an incremental version of the viterbi dynamic programming algorithm. The incremental algorithm is shown to dramatically reduce memory usage in long state sequence problems compared with the standa...
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ISBN:
(纸本)9780769530697
This paper describes an incremental version of the viterbi dynamic programming algorithm. The incremental algorithm is shown to dramatically reduce memory usage in long state sequence problems compared with the standard viterbi algorithm while having no measurable impact on the algorithms runtime. In addition, the set of problems which the viterbi algorithm can be applied is extended by the incremental algorithm to include problems of finding optimal paths in realtime domains. The viterbi algorithm is widely used to find optimal paths in hidden markov models (HMM), and HMMs are frequently applied to both streaming data problems where realtime solutions can be of interest, and to large state sequence problems in areas like bioinformatics. In this paper we apply the incremental algorithm to finding optimal paths in a variant of the burst detection HMM applied to the novel problem of detecting user activity levels in digital evidence data derived from hard drives.
viterbi algorithm is a commonly used algorithm for Gaussian filtered minimum frequency shift keying (GMSK) demodulation, but there exist some problems such as large delay, high overhead, and data overflow in the hardw...
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ISBN:
(纸本)9781728172019
viterbi algorithm is a commonly used algorithm for Gaussian filtered minimum frequency shift keying (GMSK) demodulation, but there exist some problems such as large delay, high overhead, and data overflow in the hardware implementation. Aiming at the problems of delay and overhead, we propose a novel update rule to optimize the stored transfer-state information table and realize one-step backtracking in this paper. It also ensures the realization of pipeline operation, reduces demodulation delay, and saves hardware resources. Furthermore, we adopt combinational logic to perform pre-decision, which not only satisfies the timing requirements, but also achieves the anti-overflow. The hardware implementation results demonstrate the feasibility and correctness of the design.
Vital signs are related to mental stress conditions. In particular, the variation of R-R interval (the peak-to-peak interval of heartbeats) reflects mental stress. For measuring heart rate, non-contact detection using...
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ISBN:
(纸本)9781509032549
Vital signs are related to mental stress conditions. In particular, the variation of R-R interval (the peak-to-peak interval of heartbeats) reflects mental stress. For measuring heart rate, non-contact detection using Doppler radar has been studied in many works. In this paper, we propose an algorithm to detect periodic heartbeats for some periods in which the R-R intervals are almost equal. In the long term, the R-R intervals gradually vary, however, the R-R intervals are almost equal within a short period. To detect those periods, we assume that the R-R intervals always have almost equal intervals. Then, we detect periodic peaks appearing at almost the equal intervals by using the viterbi algorithm. After detecting periodic peaks, we detect the periods during which the R-R intervals are almost equal, based on the variance of the detected peak-to-peak intervals. Moreover, we estimate an average R-R interval and find peaks that appear at the interval nearly equal to the estimated average R-R interval within each detected period. Experimental results show that the proposed algorithm improves RMSEs (root mean square error) of the R-R interval compared with the conventional methods.
Significant power reduction can be achieved by exploiting real-time variation in system characteristics while decoding convolutional codes. The approach proposed herein adaptively approximates viterbi decoding by vary...
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ISBN:
(纸本)1581134754
Significant power reduction can be achieved by exploiting real-time variation in system characteristics while decoding convolutional codes. The approach proposed herein adaptively approximates viterbi decoding by varying truncation length and pruning threshold of the T-algorithm while employing trace-back memory management. Adaptation is performed according to variations in signal-to-noise ratio, code rate, and maximum acceptable bit error rate. Potential energy reduction of 70 to 97.5% compared to viterbi decoding is demonstrated. Superiority of adaptive T-algorithm decoding compared to fixed T-algorithm decoding is studied. General conclusions about when applications can particularly benefit from this approach are given.
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