1. 非负稀疏编码 稀疏编码,sparse... ... ) non-negative sparse coding 非负稀疏编码 ) sparse linear coding 稀疏线性编码 ... www.dictall.com|基于1 个网页 例句 释义: 全部,非负稀疏编码 更多例句筛选 1. Natural image denoising method based on non-negative sparse coding shrinkage 非负稀疏编码收...
NON-NEGATIVESPARSECODINGPatrik0.HoyerKeuralNetworksResearchCentreHelsinkiUniversityofTechnologyP.O.Box9800,FIN-02015HUT,Finland..
2) Non-negative Sparse Coding(NNSC) 非负稀疏编码(NNSC)3) sparse coding 稀疏编码 1. Natural image denoising method based on nonnegative sparse coding shrinkage; 非负稀疏编码收缩法的自然图像消噪 2. Study on sparse coding speech enhancement; 基于稀疏编码的语音增强方法研究 3. Study on ...
Summary: A dispersion constraint based non-negative sparse coding (DCB-NNSC) model is discussed in this paper. To ensure the sparsity in self-adaptive, the kurtosis criterion is used to measure the sparse priori knowledge of feature coefficients. And to enhance the capability of feature ...
Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. We briefly describe the motivation behind this type of data representation and its relation to standard sparse coding and non-negative matrix factorization. We then give a simple yet efficient...
Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. In this paper we briefly describe the motivation behind this type of data representation and its relation to standard sparse coding and nonnegative matrix factorization. We then give a simple...
Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. In this paper we briefly describe the motivation behind this type of data representation and its relation to standard sparse coding and non-negative matrix factorization. We then give a simpl...
Non-negative mutative-sparseness coding (NMSC) is a method for analyzing the non-negative sparse components of multivariate data and representing the data as hierarchical structure. Specifically in a subsequent layer, the sparseness of each data is adjusted according to the corresponding hidden ...
We developed an innovative network model based on this feedback mechanism, linking entorhinal inputs to hippocampal spatial encoding cells through a non-negative sparse coding, using grid cells and weak spatial cells as inputs. Our findings demonstrate that the model learns and adjusts the ...
Non-negative sparse coding (NSC) is a powerful technique for low-rank data approximation, and has found several successful applications in signal processing. However, the temporal dependency, which is a vital clue for many realistic signals, has not been taken into account in its conventional mode...