RVM是一种稀疏贝叶斯学习（Sparse Bayesian Learning）中国科学技术大学硕士毕业论文 动态环境下的足球机器人视觉系统算法，它学习的结果只保存了较为少量的权值，在处理速度上大为提高...
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On the basis of sparse Bayesian learning,the structure features of radar imaging system are discussed and a fast super-resolution imaging algorithm based on fast Fourier transform(FFT) and block Toeplitz system is proposed.
以稀疏贝叶斯学习为基础,针对雷达成像系统的结构特点,提出了一种基于快速傅立叶变换(FFT)和分块托普里兹(Toeplitz)系统的快速超分辨成像算法。
参考来源 - 基于稀疏贝叶斯学习的雷达目标成像技术Based on a rank-1 update, we propose Sparse Bayesian Learning Algorithm (SBLA), which has low complexity and high sparseness, thus being very suitable for large-scale problems.
基于秩-1更新，提出了稀疏贝叶斯学习算法(SBLA)。 该算法具有较低的计算复杂度和较高的稀疏性，从而适合于求解大规模问题。
参考来源 - 三种有效的核机器·2,447,543篇论文数据，部分数据来源于NoteExpress
We integrate the Sparse Bayesian Learning algorithm into the SMC blind receiver to improve the performance under sparse channels.
我们将稀疏贝叶斯学习与序列蒙特卡罗盲均衡算法结合，提高了原算法的性能。
Based on a rank-1 update, we propose sparse Bayesian Learning Algorithm (SBLA), which has low complexity and high sparseness, thus being very suitable for large-scale problems.
基于秩- 1更新，提出了稀疏贝叶斯学习算法(SBLA)。该算法具有较低的计算复杂度和较高的稀疏性，从而适合于求解大规模问题。
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