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Fisher Discriminative Embedding Low-Rank Sparse Representation for Music Genre Classification
This work focuses on a music genre classification method based on a sparse low-rank representation. Sparse low-rank representation is an effective...
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Multilayer Fisher extreme learning machine for classification
As a special deep learning algorithm, the multilayer extreme learning machine (ML-ELM) has been extensively studied to solve practical problems in...
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Feature selection using neighborhood uncertainty measures and Fisher score for gene expression data classification
The classification of gene expression data provides a basis for the study of pathogenesis and treatment. However, this type of data is characterized...
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Intrusion Detection in IoT Devices Using ML and DL Models with Fisher Score Feature Selection
IoT devices are physical things that have sensors, network connectivity, and software built into them. This allows them to gather data and share it...
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Structured analysis dictionary learning based on discriminative Fisher pair
In analysis dictionary learning (ADL) algorithms, the row vectors (profiles) of the analysis coefficient matrix and analysis atoms are always...
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Fault Diagnosis of Rotating Machinery Based on Local Centroid Mean Local Fisher Discriminant Analysis
PurposeCurrently, the vibration signals collected from rotating machinery are high dimensional and massive, how to extract sensitive fault...
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An Enhanced Support Vector Machine for Face Recognition in Fisher Subspace
With the advances in technology, facial recognition has become a very popular technology to be used majorly as a security technique. Face recognition...
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The max–min newsvendor pricing problem under conditional value-at-risk criterion
This paper studies a risk-averse newsvendor pricing model with limited demand information under the conditional value-at-risk (CVaR) criterion. The...
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On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix
This paper is concerned with the analysis of optimization procedures for optimal experiment design for locally affine Takagi-Sugeno (TS) fuzzy models...
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Kernel Fisher Envelope Surface for Pattern Recognition
It is found that the batch process is more difficultly monitored compared with the continuous process, due to its complex features, such as...
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Comparison of Optimal Sensor Placement Technics for Structural Health Monitoring Application
The information value of high-rise structural health monitoring applications relies significantly on optimal sensor placement (OSP) technics as it...
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Strength and buckling analysis for cylindrical shell panels by various strength theories
The purpose of this work is to offer a comprehensive analysis of the buckling and strength of shell structures in accordance with several strength...
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Cobalt crust recognition based on kernel Fisher discriminant analysis and genetic algorithm in reverberation environment
Recognition of substrates in cobalt crust mining areas can improve mining efficiency. Aiming at the problem of unsatisfactory performance of using...
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Improved local fisher discriminant analysis based dimensionality reduction for cancer disease prediction
A good dimensional reduction technique is needed to apply and improve the effectiveness of dimensionality reduction for medical data....
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Guaranteed Significance Level Criterion in Automatic Speech Signal Segmentation
Abstract —The article considers the problem of automatic segmentation of a speech signal into phonetic units in conditions of their a priori uncertain...
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Combined Load Failure Criterion for Rock Bolts in Hard Rock Mines
Rock bolts are highly important underground to prevent falls of ground and thus, ensure safety. In situ, the ground reinforcement is subjected to a...
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The Minimum Detectable Damage as an Optimization Criterion for Performance-Based Sensor Placement
Selecting the right sensor locations is pivotal for the effectiveness of vibration-based damage detection as part of structural monitoring under...
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CL-BPUWM: continuous learning with Bayesian parameter updating and weight memory
Catastrophic forgetting in neural networks is a common problem, in which neural networks lose information from previous tasks after training on new...
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Assessing the Reliability of a Mathematical Model of Working Processes Occurring in a Hydraulic Drive
When studying the work processes occurring in the hydraulic drives of mechatronic systems of self-propelled vehicles, one of the most critical tasks...
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One-class machine learning approach for localized damage detection
With the advancement in computing power and sensing technology in the last decade, smart monitoring and decision-making approaches are becoming more...
