Adaptive Pre- and Post-Filtering for Block-Based Communication Systems

本研究涉及的理论，设计和有效的实现本地自适应时域预/后处理运营商的有效信号表示和强大的通信。时域解释导致了一个强大的信号分解和信号重建方法，具有前所未有的适应能力。该框架保留了基于块的方法的所有灵活功能，并在其上添加了高水平的自适应性：数据样本使用小的预处理/后处理块运算符进行处理，并且每个运算符都可以在必要时进行动态调整。此外，小型本地运算符很好地适合并行计算，以及快速、VLSI友好、可能无乘法器的实现。最后，时域预滤波是与传感器最接近的链接，而后滤波是与显示器/渲染器最接近的链接，这一事实允许最高级别的集成灵活性以及最经济的实施方式，只需最少的软件或硬件升级。这项研究是特别面向低复杂度的信号编码和通信算法或系统的资源受限，速度关键，和无线手持设备的实时应用。特别是，研究人员通过自适应维纳滤波技术研究局部自适应性，提供了特设的，但有效的，前/后滤波方法和基本的信息理论信号分解策略之间的关键桥梁。研究中的这种时域局部算子的目标应用包括：（i）用于低比特率编码和快速局部压缩感测的欠采样预滤波和过采样后滤波;（ii）基于变换的多描述编码;（iii）用于分组交换擦除信道的错误隐藏中的错误弹性预/后滤波器;（iv）用于密集传感器网络中的分布式信源编码的最佳变换;（iv）用于低比特率编码和快速局部压缩感测的低采样预滤波和过采样后滤波。以及（v）用于视觉数据表示和处理的自适应二维（2-D）不可分离局部分解的设计和应用。

This research involves the theory, design, and efficient implementation of locally adaptive time-domain pre-/post-processing operators for efficient signal representation and robust communications. The time-domain interpretation leads to a powerful signal decomposition and signal reconstruction approach with an unprecedented level of adapting capability. This framework retains all flexible features of block-based approaches and adds on top a high level of adaptivity: data samples are processed with small pre-/post-processing block operators and each can be adapted on-the-fly if necessary. Furthermore, small local operators lend themselves nicely to parallel computing, and fast, VLSI-friendly, possibly multiplierless, implementations. Finally, the fact that time-domain pre-filtering is the closest link to the sensor and post-filtering to the display/renderer allows the highest level of integration flexibility as well as the most economical implementation with minimum software or hardware upgrade. This research is particularly geared toward low-complexity signal coding and communication algorithms or systems in resource-constrained, speed-critical, and real-time applications for wireless hand-held devices. In particular, the investigators study local adaptivity via adaptive Wiener filtering technique, providing the critical bridge between ad-hoc, but effective, pre-/post-filtering approaches and fundamental information-theoretic signal decomposition strategies. Target applications of such time-domain local operators under investigation include: (i) under-sampled pre-filtering and over-sampled post-filtering for low bit-rate coding and fast local compressed sensing;(ii) transform-based multiple description coding; (iii) error-resilient pre-/post-filters in error concealment for packet-switched erasure channels; (iv) optimal transform for distributed source coding in a dense sensor networks; and (v) design and application of adaptive two-dimensional (2-D) non-separable local decomposition for visual data representation and processing.