Engineering Creativity Award: Maximum Likelihood Applied to Spectrum Estimation

研究涉及的工作，在频谱估计 平稳高斯分布的有限样本问题 随机过程 重点是一般方法， 获得具有小偏差和低方差的估计量。 理论工作分三个方面：1）通过 格型滤波器，2）最大熵扩展，3）复数 噪声中的指数 调查还涉及多信号 阵列处理、波束形成和延迟多普勒雷达成像 沿着这些信号处理算法的映射， 并行架构 本项目是创意奖资助项目 为工程专业本科生提供的课程。

The research deals with work in spectrum estimation for problems involving finite samples from stationary Gaussian stochastic processes. Emphasis is on the general method for achieving estimators with small bias and low variance. Theoretical work is in three areas: 1) Implementation via lattice filters, 2) Maximum-entropy extension, 3) Complex exponentials in noise. Investigations also involve multi-signal array processing, beamforming, and delay-doppler radar imaging along with mapping of these signal processing algorithms to parallel architectures. This project is one supported under the Creativity Awards for Undergraduate Engineering Students.