Energy-Efficient Time-Based Encoders and Digital Signal Processors in Continuous Time

Continuous-time (CT) data conversion and continuous-time digital signal processing (DSP) are an interesting alternative to conventional methods of signal conversion and processing. This alternative proposes time-based encoding that may not suffer from aliasing; shows superior spectral properties (e.g. no quantization noise floor); and enables time-based, event-driven, flexible signal processing using digital circuits, thus scaling well with technology. Despite these interesting features, this approach has so far been limited by the CT encoder, due to both its relatively poor energy efficiency and the constraints it imposes on the subsequent CT DSP. In this thesis, we present three principles that address these limitations and help improve the CT ADC/DSP system. First, an adaptive-resolution encoding scheme that achieves first-order reconstruction with simple circuitry is proposed. It is shown that for certain signals, the scheme can significantly reduce the number of samples generated per unit of time for a given accuracy compared to schemes based on zero-order-hold reconstruction, thus promising to lead to low dynamic power dissipation at the system level. Presented next is a novel time-based CT ADC architecture, and associated encoding scheme, that allows a compact, energy-efficient circuit implementation, and achieves first-order quantization error spectral shaping. The design of a test chip, implemented in a 0.65-V 28-nm FDSOI process, that includes this CT ADC and a 10-tap programmable FIR CT DSP to process its output is described. The system achieves 32 dB – 42 dB SNDR over a 10 MHz – 50 MHz bandwidth, occupies 0.093 mm2, and dissipates 15 µW–163 µW as the input amplitude goes from zero to full scale. Finally, an investigation into the possibility of CT encoding using voltage-controlled oscillators is undertaken, and it leads to a CT ADC/DSP system architecture composed primarily of asynchronous digital delays. The latter makes the system highly digital and technology-scaling-friendly and, hence, is particularly attractive from the point of view of technology migration. The design of a test chip, where this delay-based CT ADC/DSP system architecture is used to implement a 16-tap programmable FIR filter, in a 1.2-V 28-nm FDSOI process, is described. Simulations show that the system will achieve a 33 dB – 40 dB SNDR over a 600 MHz bandwidth, while dissipating 4 mW

MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging -- design, implementation and application on the example of DCE-MRI

Many medical imaging techniques utilize fitting approaches for quantitative parameter estimation and analysis. Common examples are pharmacokinetic modeling in DCE MRI/CT, ADC calculations and IVIM modeling in diffusion-weighted MRI and Z-spectra analysis in chemical exchange saturation transfer MRI. Most available software tools are limited to a special purpose and do not allow for own developments and extensions. Furthermore, they are mostly designed as stand-alone solutions using external frameworks and thus cannot be easily incorporated natively in the analysis workflow. We present a framework for medical image fitting tasks that is included in MITK, following a rigorous open-source, well-integrated and operating system independent policy. Software engineering-wise, the local models, the fitting infrastructure and the results representation are abstracted and thus can be easily adapted to any model fitting task on image data, independent of image modality or model. Several ready-to-use libraries for model fitting and use-cases, including fit evaluation and visualization, were implemented. Their embedding into MITK allows for easy data loading, pre- and post-processing and thus a natural inclusion of model fitting into an overarching workflow. As an example, we present a comprehensive set of plug-ins for the analysis of DCE MRI data, which we validated on existing and novel digital phantoms, yielding competitive deviations between fit and ground truth. Providing a very flexible environment, our software mainly addresses developers of medical imaging software that includes model fitting algorithms and tools. Additionally, the framework is of high interest to users in the domain of perfusion MRI, as it offers feature-rich, freely available, validated tools to perform pharmacokinetic analysis on DCE MRI data, with both interactive and automatized batch processing workflows.Comment: 31 pages, 11 figures URL: http://mitk.org/wiki/MITK-ModelFi

Clockless Continuous-Time Neural Spike Sorting: Method, Implementation and Evaluation

In this paper, we present a new method for neural spike sorting based on Continuous Time (CT) signal processing. A set of CT based features are proposed and extracted from CT sampled pulses, and a complete event-driven spike sorting algorithm that performs classification based on these features is developed. Compared to conventional methods for spike sorting, the hardware implementation of the proposed method does not require any synchronisation clock for logic circuits, and thus its power consumption depend solely on the spike activity. This has been implemented using a variable quantisation step CT analogue to digital converter (ADC) with custom digital logic that is driven by level crossing events. Simulation results using synthetic neural data shows a comparable accuracy compared to template matching (TM) and Principle Components Analysis (PCA) based discrete sampled classification

Continuous-time acquisition of biosignals using a charge-based ADC topology

This paper investigates continuous-time (CT) signal acquisition as an activity-dependent and nonuniform sampling alternative to conventional fixed-rate digitisation. We demonstrate the applicability to biosignal representation by quantifying the achievable bandwidth saving by nonuniform quantisation to commonly recorded biological signal fragments allowing a compression ratio of ≈5 and 26 when applied to electrocardiogram and extracellular action potential signals, respectively. We describe several desirable properties of CT sampling, including bandwidth reduction, elimination/reduction of quantisation error, and describe its impact on aliasing. This is followed by demonstration of a resource-efficient hardware implementation. We propose a novel circuit topology for a charge-based CT analogue-to-digital converter that has been optimized for the acquisition of neural signals. This has been implemented in a commercially available 0.35 μm CMOS technology occupying a compact footprint of 0.12 mm 2 . Silicon verified measurements demonstrate an 8-bit resolution and a 4 kHz bandwidth with static power consumption of 3.75 μW from a 1.5 V supply. The dynamic power dissipation is completely activity-dependent, requiring 1.39 pJ energy per conversion

Resource-Constrained Acquisition Circuits for Next Generation Neural Interfaces

The development of neural interfaces allowing the acquisition of signals from the cortex of the brain has seen an increasing amount of interest both in academic research as well as in the commercial space due to their ability to aid people with various medical conditions, such as spinal cord injuries, as well as their potential to allow more seamless interactions between people and machines. While it has already been demonstrated that neural implants can allow tetraplegic patients to control robotic arms, thus to an extent returning some motoric function, the current state of the art often involves the use of heavy table-top instruments connected by wires passing through the patient’s skull, thus making the applications impractical and chronically infeasible. Those limitations are leading to the development of the next generation of neural interfaces that will overcome those issues by being minimal in size and completely wireless, thus paving a way to the possibility of their chronic application. Their development however faces several challenges in numerous aspects of engineering due to constraints presented by their minimal size, amount of power available as well as the materials that can be utilised. The aim of this work is to explore some of those challenges and investigate novel circuit techniques that would allow the implementation of acquisition analogue front-ends under the presented constraints. This is facilitated by first giving an overview of the problematic of recording electrodes and their electrical characterisation in terms of their impedance profile and added noise that can be used to guide the design of analogue front-ends. Continuous time (CT) acquisition is then investigated as a promising signal digitisation technique alternative to more conventional methods in terms of its suitability. This is complemented by a description of practical implementations of a CT analogue-to-digital converter (ADC) including a novel technique of clockless stochastic chopping aimed at the suppression of flicker noise that commonly affects the acquisition of low-frequency signals. A compact design is presented, implementing a 450 nW, 5.5 bit ENOB CT ADC, occupying an area of 0.0288 mm2 in a 0.18 μm CMOS technology, making this the smallest presented design in literature to the best of our knowledge. As completely wireless neural implants rely on power delivered through wireless links, their supply voltage is often subject to large high frequency variations as well voltage uncertainty making it necessary to design reference circuits and voltage regulators providing stable reference voltage and supply in the constrained space afforded to them. This results in numerous challenges that are explored and a design of a practical implementation of a reference circuit and voltage regulator is presented. Two designs in a 0.35 μm CMOS technology are presented, showing respectively a measured PSRR of ≈60 dB and ≈53 dB at DC and a worst-case PSRR of ≈42 dB and ≈33 dB with a less than 1% standard deviation in the output reference voltage of 1.2 V while consuming a power of ≈7 μW. Finally, ΣΔ modulators are investigated for their suitability in neural signal acquisition chains, their properties explained and a practical implementation of a ΣΔ DC-coupled neural acquisition circuit presented. This implements a 10-kHz, 40 dB SNDR ΣΔ analogue front-end implemented in a 0.18 μm CMOS technology occupying a compact area of 0.044 μm2 per channel while consuming 31.1 μW per channel.Open Acces

Design and practical realization of polymorphic crosstalk circuits using 65nm TSMC PDK

Title from PDF of title page viewed January 14, 2020Thesis advisor: Mostafizur RahmanVitaIncludes bibliographical references (page 54-56)Thesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City. 2019As the technology node scales down, the coupling capacitance between the adjacent metal lines increases. With an increase in this electrostatic coupling, the unwanted signal interference also increases, which is popularly called as Crosstalk. In conventional circuits, the Crosstalk affects either functionality or performance or both. Therefore the Crosstalk is always considered as detrimental to the circuits, and we always try to filter out the Crosstalk noise from signals. Crosstalk Computing Technology tries to astutely turn this unwanted coupling capacitance into computing principle for digital logic gates[1, 2]. The special feature of the crosstalk circuits is its inherent circuit mechanism to build polymorphic logic gates[3]. Our team has previously demonstrated various fundamental polymorphic logic circuits [1-6,16-18]. This thesis shows the design of the large-scale polymorphic crosstalk circuits such as Multiplier–Sorter, Multiplier–Sorter–Adder using the fundamental polymorphic gates, and also analyzes the Power, Performance, and Area (PPA) for these large-scale designs. Similar to the basic and complex polymorphic gates, the functionality of the large-scale polymorphic circuits can also be altered using the control signals. Owing to their multi-functional embodiment in a single circuit, polymorphic circuits find a myriad of useful applications such as reconfigurable system design, resource sharing, hardware security, and fault-tolerant circuit design, etc. [3]. Also, in this thesis, a lot of studies have been done on the variability (PVT analysis) of Crosstalk Circuits. This PVT variation analysis establishes the circuit design requirements in terms of coupling capacitances and fan-in limitation that allows reliable operation of the Crosstalk gates under Process, Voltage and Temperature variations. As an example, I also elaborate on the reason for which the full adder can’t be implemented as a single gate in the crosstalk circuit-style at lower technology nodes. Though we designed a variety of basic and complex logic gates and crosstalk polymorphic gates, the biggest question is “Will these crosstalk gates work reliably on silicon owing to their new circuit requirements and technological challenges?”. Trying to answer the above question, the whole thesis is mainly focused on the physical implementation of the crosstalk gates at 65nm. I will detail the steps that we have performed while designing the crosstalk circuits and their layouts, the challenges we faced while implementing the new circuit techniques using conventional design approaches and PDK, and their solutions, specifically during layout design and verification. The other potential application of crosstalk circuits is in non-linear analog circuits: Analog-to-Digital Converter (ADC) [4], Digital-to-Analog Converter (DAC), and Comparator. In this thesis, I have shown how the deterministic charge summation principle that is used in digital crosstalk gates can also be used to implement the non-linear analog circuits.Introduction -- Polymorphic Crosstalk circuit design -- Practical realization of Crosstalk circuits -- PVT variation analysis -- Difficulties or errors in layout design and full chip details -- Potential miscellaneous applications -- Conclusion and future wor

A 77.3-dB SNDR 62.5-kHz Bandwidth Continuous-Time Noise-Shaping SAR ADC With Duty-Cycled G_m-C Integrator

This article presents a first-order continuous-time (CT) noise-shaping successive-approximation-register (NS-SAR) analog-to-digital converter (ADC). Different from other NS-SAR ADCs in literature, which are discrete-time (DT), this ADC utilizes a CT Gm-C integrator to realize an inherent anti-aliasing function. To cope with the timing conflict between the DT SAR ADC and the CT integrator, the sampling switch of the SAR ADC is removed, and the integrator is duty cycled to leave 5% of the sampling clock period for the SAR conversion. Redundancy is added to track the varying ADC input due to the absence of the sampling switch. A theoretical analysis shows that the 5% duty-cycling has negligible effects on the signal transfer function (STF) and the noise transfer function. The output swing and linearity requirements for the integrator are also relaxed thanks to the inherent feedforward path in the NS-SAR ADC architecture. Fabricated in 65-nm CMOS, the prototype achieves 77.3-dB peak signal-to-noise and distortion ratio (SNDR) in a 62.5-kHz bandwidth while consuming 13.5μ W, leading to a Schreier figure of merit (FoM) of 174.0 dB. Moreover, it provides 15-dB attenuation in the alias band.</p

Discrete-Time Mixing Receiver Architecture for RF-Sampling Software-Defined Radio

A discrete-time (DT) mixing architecture for RF-sampling receivers is presented. This architecture makes RF sampling more suitable for software-defined radio (SDR) as it achieves wideband quadrature demodulation and wideband harmonic rejection. The paper consists of two parts. In the first part, different downconversion techniques are classified and compared, leading to the definition of a DT mixing concept. The suitability of CT-mixing and RF-sampling receivers to SDR is also discussed. In the second part, we elaborate the DT-mixing architecture, which can be realized by de-multiplexing. Simulation shows a wideband 90° phase shift between I and Q outputs without systematic channel bandwidth limitation. Oversampling and harmonic rejection relaxes RF pre-filtering and reduces noise and interference folding. A proof-of-concept DT-mixing downconverter has been built in 65 nm CMOS, for 0.2 to 0.9 GHz RF band employing 8-times oversampling. It can reject 2nd to 6th harmonics by 40 dB typically and without systematic channel bandwidth limitation. Without an LNA, it achieves a gain of -0.5 to 2.5 dB, a DSB noise figure of 18 to 20 dB, an IIP3 = +10 dBm, and an IIP2 = +53 dBm, while consuming less than 19 mW including multiphase clock generation