Analog-Inspired Digital Signal Processors

身份证号：0701766标题：模拟启发的数字信号处理器PI：Yannis TsividisInst：哥伦比亚大学，纽约，纽约摘要当今科学和技术领域中一些最具创新性的工作发生在不同领域之间。虽然某些领域本身可能已经成熟，但这些领域之间的联系可能是新的，并可能为研究提供丰富的可能性。我们工作背后的动机是相信，当一个领域内的不同领域相结合时，可以获得类似的好处;在我们的案例中，该领域是信号处理。这项工作的主要应用领域是数字信号处理器，即处理由1和0组成的数字信号的硬件，例如在现代计算机中可以找到。这个跨学科工作的第二个领域是模拟信号和系统，即在物理世界中出现的信号，以及用于处理它们的系统。这项工作有两个组成部分。第一个组件使用“压缩-扩展”的概念，该概念在过去已经非常成功地应用于用于语音传输和音频记录的模拟系统（例如，杜比系统（Dolby System）这个过程动态地改变信号的幅度，以确保它们总是足够大，从而不会被噪声污染。这种技术直接应用于数字信号处理器完全失败，因为它没有考虑到这种处理器内部的动态。PI正在开发一个通用的数学框架来消除这个问题，使用外部线性，内部非线性系统的概念，这已经在之前的NSF资助下为模拟系统开发了。这些结果可以用于从定点类型的数字信号处理器获得更好的性能，而不必增加其中使用的位数，从而保持它们的功耗低，这在无处不在的便携式应用中是一个关键优势，这需要电池的低能量消耗。对于实时信号处理应用，信号仍然是1和0，但是是针对所有时间定义的，而不是像在经典计算和数字信号处理中那样在离散时刻定义。我们正在开发一种理论来处理这种信号，并研究使用它们的系统的特性。初步工作表明，连续时间操作可以使低得多的误差成为可能，并且还可以使具有依赖于信号的功率耗散的硬件成为可能，其中功率随着信号活动的减少而向零减小。同样，这种技术的一个关键优势是在便携式应用中的低能耗。该计划是充分测试的想法与硅芯片定制设计的目的。

ID: 0701766 Title: Analog-Inspired Digital Signal ProcessorsPI: Yannis TsividisInst: Columbia University, New York, NYABSTRACTSome of the most innovative work in science and technology today occurs at the boundaries between fields. Although certain fields may be mature in themselves, the connection of such fields can be new, and can present a wealth of possibilities for research. The motivation behind our work is the conviction that similar benefits can be had when different domains within a single field are combined; in our case, that field is signal processing. The main domain of application of this work is digital signal processors, i.e. hardware that processes digital signals consisting of ones and zeros, which are for example found in modern computers. The second domain in this cross-disciplinary work is analog signals and systems, i.e. signals as they occur in the physical world, and the systems that are used to handle them. The work has two components. The first component uses the concept of accompanding" (compressing-expanding), which has been very successfully applied in the past to analog systems for voice transmission and audio recording (e.g., in the ubiquitous Dolby system). This process varies the magnitude of signals dynamically, to ensure that they are always large enough so that they do not get contaminated by noise. Direct application of this technique to digital signal processors fails completely, as it does not take into account the dynamics inside such processors. The PI is developing a general mathematical framework for eliminating this problem, using concepts from externally linear, internally nonlinear systems, which has been already developed for analog systems under prior NSF funding. The results can be used to obtain much better performance from digital signal processors of the fixed-point kind, without having to increase the number of bits used in them, thus keeping their power dissipation low a key advantage in the ubiquitous portable applications, which require low energy drain from a battery.The second component of the work uses digital signals as functions of continuous time, for real-time signal processing applications; the signals are still ones and zeros, but are defined for all time, rather than at discrete time instants as in classical computing and digital signal processing. We are developing a theory to handle such signals and study the properties of the systems that use them. Preliminary work has shown that continuous-time operation can make possible a much lower error, and in addition makes possible hardware which has signal-depended power dissipation, with the power decreasing toward zero as the signal activity decreases. Again, a key advantage of this technique is the low energy drain in portable applications. The plan is to fully test ideas with a silicon chip custom-designed for this purpose.