Advanced Image Processing Algorithms for Breast Cancer Decision Support and Information Management System

Garcia, Michael; López-Linares, Karen; Rampun, Andrik; Scotney, Bryan; Morrow, Philip; Salmon, R; Garbey, Marc; Audersch, Stefan; Azpíroz, Marina; Romero, Juan Antonio Martos; Belloch, Vicente; Santabárbara, José Manuel; Macía, Iván

doi:10.1007/978-981-13-8566-7_14

Cited by 1 publication

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“…e music signal is processed segmentally according to the structure of the sparse music signal, which not only meets the needs of the sensing device, but also captures the structure of the music signal in addition to the sparseness, and this method provides an additional key factor for music signal recovery. García et al [16] proposed an advanced iterative development of tensor-based matrices, which can both serve as sparse bases to model the structural information present in all musical signal dimensions and represent measurement protocols used in distributed settings. Tensor-based compressed sensing enables distributed acquisition and measurement of music signals, extending the application scope of advanced iterative development (e.g., sensor networks).…”

Section: Related Workmentioning

confidence: 99%

Research on the Development of Localized Music Curriculum System Based on the Theory of Multiple Intelligences

Gong

2022

Scientific Programming

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The integration and development of music curriculum signals have attracted the attention of researchers in real teaching scenarios. Based on the theory of multiple intelligences algorithm, this paper constructs a music curriculum integration and development model. This paper establishes a nonnegative matrix decomposition scheme, adds a constraint term that can reflect the smoothness of the time-varying gain matrix to the divergence-based objective function, and iteratively solves the problem of curriculum integration and development through the minimum optimization algorithm obtained by constructing the auxiliary function. In the process of simulation experiment, the optimal solution of each factor matrix was designed, the source music signal was reconstructed, and the sufficiently sparse source music signal was separated. The experimental results show that, compared with the parameter estimation without preprocessing, the parameter estimation with preprocessing is more accurate, the accuracy of the improved algorithm reaches 97.1%, the signal compression ratio reaches 0.656, and the enhanced signal can obtain at most 6 dB. The signal-to-noise ratio is improved, and the convergence speed is fast and asymptotically reaches the lower bound. It is suitable for parameter estimation of low-order and high-order autoregressive processes and effectively promotes the smooth development of music course signals.

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Section: Related Workmentioning

confidence: 99%

Research on the Development of Localized Music Curriculum System Based on the Theory of Multiple Intelligences

Gong

2022

Scientific Programming

View full text Add to dashboard Cite

show abstract

Advanced Image Processing Algorithms for Breast Cancer Decision Support and Information Management System

Cited by 1 publication

References 30 publications

Research on the Development of Localized Music Curriculum System Based on the Theory of Multiple Intelligences

Research on the Development of Localized Music Curriculum System Based on the Theory of Multiple Intelligences

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