1 Brandon Rumberg West Virginia University Analog Filter Banks.

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Presentation transcript:

1 Brandon Rumberg West Virginia University Analog Filter Banks

2 Themes of this talk Analog VLSI –Analog audio processing Analog filter-bank –Relation to wavelets –Relation to cochlea Computation based on physics of devices

3 Ubiquitous Sensors Sensors are extremely: –Small –Cheap Devices are: –Small –Battery powered –Always on With bench top sensors it wouldn't be an issue

4 Analog VLSI Relation to traditional analog –Not just op-amps and data converters –Perform computation Standard CMOS –Piggy-back on digital developments –Weak inversion (sub-threshold)‏

5 Analog VLSI Low power –Subthreshold Fewer transistors Small Complex operations based on physics Lack of precision –Resolution dynamic range –Noise –Nonlinearity –Biases Lack of programming –Hard to reuse earlier work Difficult to design

6 Subthreshold Weak inversion –Exponential relationship –Low currents 0.1pA 1μA

7 Floating Gates Nonvolatile memory Biasing problem Add some reconfigurability –Program bias currents Adaptation –Learning –Neural Nets

8 Neuromorphic Biologically inspired –Humans great at: Perception Adaptation Efficient Historically related to Analog VLSI

9 Analog VLSI for Audio Processing Analog/Digital Synergy Analog: General Tasks Digital: Specific Tasks

10 Analog Filter Bank Array of resonators Relation to wavelets –Constant relative bandwidth –Similar algorithms? Time resolution vs. frequency resolution –Resonance

11 Cochlea Frequency Decomposition Position dependent frequency response Exponential tap spacing

12 Silicon Cochleae Cochlea resonators aren't independent

13 Quality Factor Resonance Possibility to do adaptive Q‏ C4

14 BPF Design Struggle for high precision –Limited by noise and nonlinearities Has to work across audio range –3 orders of magnitude change in frequency –3 orders of magnitude change in current Limited by programming precision and transition to strong inversion

15 Filter Bank Questions How many taps? How much Q? Phase? Orthogonal filters? Reconstruction? What is the output?

16 Response to Sine

17 Two Tones

18 Response to Speech

19 Response to Pulse

20 Speech Spectrogram Circuit ModelFFT

21 Frequency Response

22 Analog Sub-band Processing Peak detector Vector-matrix multiplier Comparator Rectifier Differentiator Nonlinear –tanh –sinh

23 To do... Analytic characterization of analog filter banks Full portfolio of sub-band processing structures DSP back-ends –Full system –Algorithms

24 ?