Matrix Mappings on the Domains of Invertible Matrices by Muhammed Altun

“…We show that the characterization of a random matrix operator , where and are matrix domains with invertible matrices and , can be reduced to the characterization of the operator . …”
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Statistical covariance blind detection algorithm based on cholesky factorization in cognitive radio network by Ying-xue LI, Shu-qun SHEN, Lang-tao HU, Qiu-cai WANG

“…As the blind covariance detection algorithm has the shortcoming that the performance parameters are obtained using non-asymptotic method,a new blind detection algorithm was presented using cholesky factorization.Utilizing random matrix theory,the performance parameters was derived using non-asymptotic method.The proposed method overcomes the noise uncertainty problem and performs well without information about the channel,primary user and noise.Numerical simulation results demonstrate that the performance parameters expressions are correct and the new detector outperforms the other blind covariance detectors.…”
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Tridiagonal Hamiltonians modeling the density of states of the double-scaled SYK model by Pratik Nandy

“…Our numerical results are further corroborated by semi-analytical findings, a random matrix potential construction in the bulk, and the analytic results at the edge of the Lanczos spectra using the method of moments.…”
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A novel fuzzy vault scheme based on the feature level fusion of fingerprint and face features by Xun LI, Lin YOU, Jiahao LIANG, Chunhui YAN

“…Aiming at the problem that the biometric feature-based fuzzy vault is vulnerable to correlation attack and the loss of key and biometric template,and the authentication performance of fuzzy vault based on single biometric feature is unreliable,a novel fuzzy vault scheme based on the feature level fusion of fingerprint and face features was proposed.This scheme carried out irreversible transformation of fingerprint features and face features,and based on the Diffie-Hellman algorithm,the transformed fingerprints and face features were fused into a template at the feature level.Finally,the fusion template was used to construct the fuzzy vault.By updating the random matrix,the vault could be revoked,which could effectively resist the correlation attacks and achieve reliable authentication.Experimental results show that the proposed scheme improves the reliability of the system and the security of multiple biometric templates.…”
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Tail Bounds for ℓ1 Norm of Gaussian Random Matrices with Applications by Xianjie Gao, Mingliang Zhang, Jinming Luo

“…As major components of the random matrix theory, Gaussian random matrices have been playing an important role in many fields, because they are both unitary invariant and have independent entries and can be used as models for multivariate data or multivariate phenomena. …”
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A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks by Yongwei Zhang, Pin Wan, Shunchao Zhang, Yonghua Wang, Nan Li

“…In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. …”
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Disorder-free Sachdev-Ye-Kitaev models: Integrability and a precursor of chaos by Soshun Ozaki, Hosho Katsura

“…Conversely, our analysis shows no evidence of random-matrix behavior in level spacing statistics or the spectral form factor. …”
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The Exact Distribution of the Condition Number of Complex Random Matrices by Lin Shi, Taibin Gan, Hong Zhu, Xianming Gu

“…Let Gm×n (m≥n) be a complex random matrix and W=Gm×nHGm×n which is the complex Wishart matrix. …”
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Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise by Jean Barbier, Francesco Camilli, Yizhou Xu, Marco Mondelli

“…In this paper, using tools from statistical physics (replica method) and random matrix theory (generalized spherical integrals) we establish the characterization of the information-theoretic limits for a noise matrix drawn from a general trace ensemble. …”
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RMT Assessments of the Market Latent Information Embedded in the Stocks' Raw, Normalized, and Partial Correlations by Dror Y. Kenett, Yoash Shapira, Eshel Ben-Jacob

“…We compared the Zipf plot, spectrum, and distribution of the eigenvalues for each matrix with the results of the corresponding random matrix. The analysis was performed on stocks belonging to the New York and Tel Aviv Stock Exchange, for the time period of January 2000 to March 2009. …”
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Testing the significance of pricing factors of oil and gas companies. by Antonio Garcia-Amate, Laura Molero-González, Miguel Angel Sánchez-Granero, Juan Evangelista Trinidad-Segovia, Andres García-Medina

“…Through a new approach from the Random Matrix Theory, the aim is to know how many are the factors that explain the market performance of the O&G subsectors (upstream, midstream & downstream), and also if the Brent price can be considered an explanatory factor. …”
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An Effective Method of Monitoring the Large-Scale Traffic Pattern Based on RMT and PCA by Jia Liu, Peng Gao, Jian Yuan, Xuetao Du

“…In this paper, a method based on Random Matrix Theory (RMT) and Principal Components Analysis (PCA) is proposed for monitoring and analyzing large-scale traffic patterns in the Internet. …”
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Unveiling multiscale spatiotemporal dynamics of volatility in high-frequency financial markets. by Fangyan Ouyang, Wenyan Peng, Tingting Chen

“…After constructing cross-correlation matrices for each time scale, we analyze the eigenvalues, eigenvectors, and probability distribution of Cij based on Random Matrix Theory. Notably, we find stronger correlations between stocks at higher frequencies, with distinct eigenvector patterns associated with large eigenvalues across different time scales. …”
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Performance Analysis of Large-Scale Digital Phased Array Mixed-ADC Receiver in Compact Space by ZHANG Yi, GAO Hang, MA Song, GUO Hongru, XIA Bin, ZHANG Chaoxian

“…Then, used a linear maximum ratio combining receiver and based on random matrix theory, a closed form expression for the achievable rate of the system under a given antenna array topology was derived. …”
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Thermal pseudo-entropy by Pawel Caputa, Bowen Chen, Tadashi Takayanagi, Takashi Tsuda

“…We have studied its properties in various quantum mechanical setups, Schwarzian theory, Random Matrix Theories, and 2D CFTs, including symmetric orbifolds. …”
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Optimal network sizes for most robust Turing patterns by Hazlam S. Ahmad Shaberi, Aibek Kappassov, Antonio Matas-Gil, Robert G. Endres

“…To address these issues, we employ random matrix theory to analyze the Jacobian matrices of larger networks with robust statistical properties. …”
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Two transitions in complex eigenvalue statistics: Hermiticity and integrability breaking by Gernot Akemann, Federico Balducci, Aurélia Chenu, Patricia Päßler, Federico Roccati, Ruth Shir

“…Open quantum systems have complex energy eigenvalues which are expected to follow non-Hermitian random matrix statistics, when chaotic, or two-dimensional (2d) Poisson statistics, when integrable. …”
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Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

“…ObjectiveIn response to challenges such as large sampling data, extended diagnosis time, and subjective fault feature selection in traditional bearing fault diagnosis, a CS-DMKELM intelligent diagnosis model for rolling bearings is proposed based on compressed sensing(CS) and deep multi-kernel extreme learning machine(D-MKELM) theory.MethodsFirstly, sparse signals were obtained through threshold processing of transformed domain signals. A Gaussian random matrix was employed as the measurement matrix to compress the processed data. …”
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Source enumeration via RMT estimator with adaptive decision criterion based on linear shrinkage estimation of noise eigenvalues using relatively few samples by Huiyue Yi

“…Abstract Estimating the number of signals embedded in noise is a fundamental problem in array signal processing. The classic random matrix theory (RMT) estimator based on RMT does not consider the bias term of the expectation of the eigenvalue being tested, and thus, its detection performance will be affected by this bias term, and it also suffers from noise uncertainty in its decision threshold. …”
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Analysis of Stationary Random Responses for Non-Parametric Probabilistic Systems by Y. Zhao, Y.H. Zhang, J.H. Lin, W.P. Howson, F.W. Williams

“…A numerical example shows that the dynamic responses calculated using a conventional (mean) finite element model may be quite different from those based on a random matrix model. For precise fabrication, the uncertainties of models cannot be ignored and the proposed method should be useful in the analysis of such problems.…”
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