Pattern Recognition and Classification
Classification complexity in myoelectric pattern recognition
... [13]. Classification complexity estimation was not investi- gated in the aforementioned studies, but algorithms intended to quantify attributes relevant to the com- plexity of pattern recognition ...
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Unsupervised Pattern Recognition for the Classification of EMG Signals
... a classification criterion will fail in the case of irregular firing patterns as they may be recorded in several ...for classification are rather inflexible because of using a fixed threshold and they will ...
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Road Functional Classification Using Pattern Recognition Techniques
... a classification model based on Pattern Recognition techniques, considering 13 input variables that, depending on their assumed value, direct the analyst towards one of the four functional classes ...
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On the Role of Genetic Algorithms in the Pattern Recognition Task of Classification
... of pattern recognition? Given primitive mechanics, can Genetic Algorithms match or exceed the performance of theoretically-based methods? Can we build a generic universal Genetic Algorithm for ...
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Pattern recognition techniques applied to rust classification in steel structures
... of classification of rust steel surfaces. Various Pattern recognition methods are studied for classifying less subjective steel surfaces from a time corrosion ...network pattern ...
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Pattern recognition using genetic programming for classification of diabetes and modulation data
... called pattern recognition. A standard pattern recognition system can be divided into two main components, feature extraction and pattern classi- ...modern pattern ...
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Induction Motor Fault Classification using Pattern Recognition Neural Network
... using pattern recognition techniques,” in 2008 IEEE 2nd International Power and Energy Conference, 2008, ...faults classification-dynamic eccentricity and broken bar faults,” in 8th IEEE Symposium on ...
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
... Supervised Classification Technique for Real Time Electromyography Pattern Recognition” is the result of my own research except as cited in the ...
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A new pattern recognition methodology for classification of load profiles for ships electric consumers
... new pattern recognition methodology is presented for the classification of the daily chronological load curves of ship electric consumers (equipment) and the determination of the respective typical ...
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A Pattern Recognition Neural Network Model for Detection and Classification of SQL Injection Attacks
... Abstract— Thousands of organisations store important and confidential information related to them, their customers, and their business partners in databases all across the world. The stored data ranges from less ...
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Pattern recognition applied to the acquisition of a grammatical classification system from unrestricted English text
... Proceedings Paper: Atwell, E and Drakos, NF (1987) Pattern recognition applied to the acquisition of a grammatical classification system from unrestricted English text. In: Maegaard, B, (ed.) ...
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Improved pattern recognition classification accuracy for surface myoelectric signals using spectral enhancement
... the classification accuracy of pattern recognition: Minimum Statistics Noise Estimation (MSNE) and Improved Minima Controlled Recursive Averaging ...reduction, classification accuracy is used ...
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Non-destructive characterisation and classification of ceramic artefacts using pEDXRF and statistical pattern recognition
... whether pattern recognition methods can be applied to the data obtained by this method in a way as in provenance ...their classification according to elem- ental compositions and well-known ...
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Novel pattern recognition methods for classification and detection in remote sensing and power generation applications
... RF classification ap- proach was focused on the constant-voltage control strategy and even though this approach can obviously obtain different accuracies with respect to the SVM-based method on specific individual ...
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A Comprehensive and Experimental Survey on Medical Data Classification and Pattern Recognition R. Subathra Devi
... data classification and pattern recognition ...data classification methods majorly divided into three categories such as supervised, classification and also semi-supervised ...
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Improved pattern recognition classification accuracy for surface myoelectric signals using spectral enhancement
... a pattern recognition-based myoelectric control ...gesture classification accuracy was shown to ...the classification accuracy is greatest when Improved Minima-Controlled Recursive Averaging ...
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A Cognizance Discovery of Indian Railway through Modern Lucrative using Pattern Recognition and Classification
... set Classification on the basis of Time Duration Factor of Data ...demography Classification may varying from Query to Query and there are a huge number of queries among which the best of the variation for ...
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CS 688 Pattern Recognition Lecture 4. Linear Models for Classification
... The result can be generalized to the multiclass case: the maximum likelihood estimate of is given by the fraction of points in the training set that belong to. Maximum likelihood [r] ...
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Spike pattern recognition by supervised classification in low dimensional embedding space
... The proposed method first models coarsely the shape of the spike by breaking down the EEG signal around major peaks into half-waves. Thresholding of shape characteris- tics extracted from the half-waves, such as ...
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Brain Tumor Classification Using Pattern Recognition Techniques: the Comprehensive Review
... B. Feature dimensionality reduction using Principal Component Analysis Excessive features increase computation times and storage memory. Furthermore, they sometimes make classification more complicated, which is ...
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