A robust analog interface system for submicron CMOS video DSP

Redman-White, W.; Duffee, R.; Bramwell, S.; Rijns, H.; James, Stephen W.; Tijou, J.; Weide, G. van der

doi:10.1109/4.701264

Cited by 7 publications

(1 citation statement)

References 5 publications

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“…Multifiber nerve recordings can be corrupted by large amounts of periodic sinusoidal oscillations at multiples of the 60-Hz line frequency [27]. The typical way to remove line noise is by notch filtering [28].…”

Section: Separation Of Artifacts From Multifiber Recordingsmentioning

confidence: 99%

Detection of Multifiber Neuronal Firings: A Mixture Separation Model Applied to Sympathetic Recordings

Tan

Taylor

Ler

et al. 2009

IEEE Trans. Biomed. Eng.

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Sympathetic nervous flow to the vasculature plays a critical role in control of regional blood flow; however, traditional processing methods of multifiber recordings cannot reliably discriminate physiologically irrelevant information from actual nerve activity, and alternative wavelet methods suffer from subjectivity and lack of a well-specified model. We propose an algorithm that allows objective threshold selection under general assumptions regarding the sparsity and statistical structure of the neural signal and noise. Our study shows that the conditional expectation of the actual nerve signal can be estimated and used to maximize the signal-to-noise ratio (SNR). We evaluated the algorithm’s performance on artificial datasets and on actual multifiber recordings (44 datasets from 22 subjects, and 1 set from a rat). On artificial datasets, the algorithm identified 70% and 80% of the spikes at −3.5 and 0.5 dB SNR with a good match between the actual and estimated spike count (R2 = 0.719, p < 0.001). On actual recordings, the overall improvement in performance compared to that of a traditional processing method was significant (t = 3.88; p = 0.0002). Our results show the applicability of this algorithm to multifiber recordings not only in humans, but also in other species.

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Section: Separation Of Artifacts From Multifiber Recordingsmentioning

confidence: 99%

Detection of Multifiber Neuronal Firings: A Mixture Separation Model Applied to Sympathetic Recordings

Tan

Taylor

Ler

et al. 2009

IEEE Trans. Biomed. Eng.

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High-PSR sync separator for TV signals

Wang

Hsu

Huang

et al. 2009

Analog Integr Circ Sig Process

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This paper presents a novel NTSC video sync separator (NSS) with a high-PSR (power supply rejection) bias generation circuitry (BGC) which comprises a temperature compensation circuitry. The proposed BGC utilizes step-down regulators and a bandgap-based bias with cascode current control. The clamping voltages required for sync separation from an NTSC signal are generated. Detailed PSR analysis of the proposed BGC is also derived to circumscribe the clamping voltage variation. The proposed design is carried out using 0.35 lm 2P4M CMOS process. The measurement results verify that the HSYNC, the composite signal, and the Line 21 caption data can be separated successfully even if a 1 V noise is coupled in the supply voltage. The measured power consumption of the proposed chip is 31.92 mW.

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