A low-power system for audio noise suppression: a cooperative analog-digital signal processing approach
David V. Anderson, P. Hasler, R. Ellis, Heejong Yoo, David W. Graham, M. Hans
Abstract
David V. Anderson, P. Hasler, R. Ellis, Heejong Yoo, David W. Graham, M. Hans
Abstract
In this papec we innoduce the concepr of cooperative nnolog-digital signnlpmcessing, and its opplicalion in rhe developmenr of (I real-time noire suppremion system. 7he olgo”thm implememed is designed lo reduce staI i o n q background noise while preserving :he non-stalionam signal component 7he oigorirhm is based on digital signal processing fouridorions :ha: are slightly odjusledfor use in rhe cominuous-time domain. Because the splsreni relies on analog compulnlion mther lhon digital, it has benej t r mch as exrreniely low power consumplion and real-time compuraion. The onolog circuit elements am based on new~poatisg~gole circuits :hat ore small. eficient, mdprogrammable-akin8 i f possible to se: and tune bias points, dffsets, ondjlrerporomelers under digital conrrol. 1. COOPERATWE ANALOG-DIGITAL SIGNAL PROCESSING New advances in analog VLSI circuits have made it possible to perform operations that more closely reflect those done in DSP applications, or that are desired in future DSP applications [ I , 2, 3, 4, 5 , 6, 71. Fulther, analog circuits and systems can be pmgrummuble, reconfigurable, adaptive, and at a density compdmble to digital memories (for example, 100,000+ multipliers on a single chip) [ B , 9, IO, 1 I , 51. These properties have been almost exclusively associated with digital processing, but the addition of small, dense, programmable analog circuits provides a framework in which to create cooperative analogdigital signal processing systems that benefit from both approaches to make something better than the sum of its parts. We define cooperative analog-digital signal processing (CADSP) as the research field using combinations of programmable analog signal processing and digital signal processing techniques for real-world processing. Neither analog signal processing nor digital signal processing can exist in current technologies without the other; that is. realworld signals are analog while much of the modem control and communication is digital. Therefore, a primary question is where to parlition the analog-digital boundry to enhance the overall functionality of a system by utilizing analog/digital computations in mutually beneficial way (Figure I) . CADSP allows more freedom of movement for the partition between the analog and digital computation. CADSP is a superset of mixed-signal research in that it focuses heavily on algorithms as well as circuit implementation. By adding functionality to our analog systems, we enhance the capabilities of the controlling digital system, and therefore, the entire product under consideration. A full discussion of this partition problem can and will encompass several research papers. The range of applications for these approaches reaches from auditory and speech processing, to beam-forming, multidimensional signal ..... ~~~ ......... ~.~ . ...... ~...
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In this papec we innoduce the concepr of cooperative nnolog-digital signnlpmcessing, and its opplicalion in rhe developmenr of (I real-time noire suppremion system. 7he olgo”thm implememed is designed lo reduce staI i o n q background noise while preserving :he non-stalionam signal component 7he oigorirhm is based on digital signal processing fouridorions :ha: are slightly odjusledfor use in rhe cominuous-time domain. Because the splsreni relies on analog compulnlion mther lhon digital, it has benej t r mch as exrreniely low power consumplion and real-time compuraion. The onolog circuit elements am based on new~poatisg~gole circuits :hat ore small. eficient, mdprogrammable-akin8 i f possible to se: and tune bias points, dffsets, ondjlrerporomelers under digital conrrol. 1. COOPERATWE ANALOG-DIGITAL SIGNAL PROCESSING New advances in analog VLSI circuits have made it possible to perform operations that more closely reflect those done in DSP applications, or that are desired in future DSP applications [ I , 2, 3, 4, 5 , 6, 71. Fulther, analog circuits and systems can be pmgrummuble, reconfigurable, adaptive, and at a density compdmble to digital memories (for example, 100,000+ multipliers on a single chip) [ B , 9, IO, 1 I , 51. These properties have been almost exclusively associated with digital processing, but the addition of small, dense, programmable analog circuits provides a framework in which to create cooperative analogdigital signal processing systems that benefit from both approaches to make something better than the sum of its parts. We define cooperative analog-digital signal processing (CADSP) as the research field using combinations of programmable analog signal processing and digital signal processing techniques for real-world processing. Neither analog signal processing nor digital signal processing can exist in current technologies without the other; that is. realworld signals are analog while much of the modem control and communication is digital. Therefore, a primary question is where to parlition the analog-digital boundry to enhance the overall functionality of a system by utilizing analog/digital computations in mutually beneficial way (Figure I) . CADSP allows more freedom of movement for the partition between the analog and digital computation. CADSP is a superset of mixed-signal research in that it focuses heavily on algorithms as well as circuit implementation. By adding functionality to our analog systems, we enhance the capabilities of the controlling digital system, and therefore, the entire product under consideration. A full discussion of this partition problem can and will encompass several research papers. The range of applications for these approaches reaches from auditory and speech processing, to beam-forming, multidimensional signal ..... ~~~ ......... ~.~ . ...... ~...
Key concepts: Digital signal processing, Analogue electronics, Computer science, Audio signal processing, Analog multiplier, Analog signal, Audio electronics, Signal processing