NYI: Dedicated VLSI Digital Signal and Image Processors

Parhi的研究方向是设计专用的高性能数字信号和图像处理器。重点是实时处理，即样品从源处收到时就进行处理，而不是存储在缓冲区中然后分批处理。递归信号处理算法拓扑的设计曾经被认为是一个主要的挑战。利用放松的前瞻性技术，新的并发算法和拓扑被开发用于自适应LMS和晶格滤波器，级联和晶格递归数字滤波器，以及预测语音和图像编码器。波数字滤波器、决策反馈均衡器和自适应差分矢量量化器的并发拓扑设计正在进行中。在霍夫曼和算术编码器（用于无损压缩）的解码速度是有限的，由于反馈。对于霍夫曼解码器，码字长度多重性约束正在被利用来设计码，其中多个比特可以同时并行解码。通过使用条件编码，进一步提高了解码器的性能。设计并行算术编码器的新方法也在研究中。

Parhi Research efforts are directed towards the design of dedicated, high-performance digital signal and image processors. The emphasis is on real-time processing, where samples are processed as they are received from the source, as opposed to being stored in buffers and then processed in batch. Design of algorithm topologies for recursive signal processing algorithms were once considered a major challenge. Using the relaxed look-ahead technique, new concurrent algorithms and topologies for adaptive LMS and lattice filters, cascade and lattice recursive digital filters, and predictive speech and image coders have been developed. Design of concurrent topologies for wave digital filters, decision-feedback equalizers, and adaptive differential vector quantizers are being pursued. The decoding speed in Huffman and arithmetic coders (used for lossless compression) is limited due to the feedback. For the Huffman decoder, the codeword length multiplicity constraint is being exploited to design codes where multiple bits can be simultaneously decoded in parallel. The performance of these decoders is further improved by the use of conditional coding. Novel approaches for design of parallel arithmetic coders are also being pursued.