NYI: Dedicated VLSI Digital Signal and Image Processors

帕尔希 研究工作是针对专用的，高性能的数字信号和图像处理器的设计。 重点是实时处理，即在从源接收样本时对其进行处理，而不是将其存储在缓冲区中，然后批量处理。 递归信号处理算法的算法拓扑设计曾经被认为是一个主要的挑战。 使用宽松的前瞻技术，新的并发算法和拓扑结构的自适应LMS和格型滤波器，级联和格型递归数字滤波器，预测语音和图像编码器已经开发。 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结构的设计正在进行中。 由于反馈，霍夫曼和算术编码器（用于无损压缩）中的解码速度受到限制。 对于霍夫曼解码器，利用码字长度多重性约束来设计其中可以并行地同时解码多个比特的代码。 这些解码器的性能通过使用条件编码而进一步提高。 并行算术编码器设计的新方法也在追求。

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.