Noise-shaping Properties Research Articles

Analysis and simulation of a novel speed estimation method based on oversampling and noise shaping techniques

Angle measurement is widely used in the servo positioning and speed control of electrical drives, where optical encoders are employed as sensors and coupled to microcontrollers with complex peripherals to provide effective position and speed measurement methods. These methods can achieve high precision and fast response, but are not particularly efficient with computer resources and require high computational costs. Therefore, fast timers, encoder signal oversampling, and a complex post-processing algorithm are used together in a recent research work to achieve a high-precision speed estimation method. Our work will prove that encoder outputs share the oversampling and noise shaping properties typical of sigma-delta modulated signals if they are sampled regularly. Based on this, a new simple and accurate speed estimation method is proposed. Here, encoder outputs are synchronously sampled, differenced, and low-pass filtered. As a result, the speed estimation circuit and its interface with the control unit are greatly simplified, while high accuracy can be achieved. A detailed mathematical analysis of the proposed technique is also performed, and the results obtained are validated by means of a simulation environment using Matlab&Simulink.

Delta modulation ([formula omitted]-M) via second-order sliding-mode control technique

In modern data acquisition and communication technologies, the differential coding scheme known as Delta Modulation (Δ-M) is being rediscovered as an efficient 1-bit analog-to-digital conversion and compression technique due to its simplicity in implementation, high resolution and minimal data throughput rate. In this paper it is proposed a second-order Δ-M scheme based on the second-order “suboptimal” sliding mode control technique. As compared to the traditional Δ-M scheme, based on the first-order sliding mode control paradigm, it yields better accuracy and noise-shaping properties as well as higher signal-to-noise ratio. Various dynamical features of the proposed scheme are investigated, both in continuous and discrete time domains, and the appropriate stability conditions are derived. Finally, numerical simulations are extensively discussed to corroborate the theoretical analysis.

Spiking, Bursting, and Population Dynamics in a Network of Growth Transform Neurons.

This paper investigates the dynamical properties of a network of neurons, each of which implements an asynchronous mapping based on polynomial growth transforms. In the first part of this paper, we present a geometric approach for visualizing the dynamics of the network where each of the neurons traverses a trajectory in a dual optimization space, whereas the network itself traverses a trajectory in an equivalent primal optimization space. We show that as the network learns to solve basic classification tasks, different choices of primal-dual mapping produce unique but interpretable neural dynamics like noise shaping, spiking, and bursting. While the proposed framework is general enough, in this paper, we demonstrate its use for designing support vector machines (SVMs) that exhibit noise-shaping properties similar to those of modulators, and for designing SVMs that learn to encode information using spikes and bursts. It is demonstrated that the emergent switching, spiking, and burst dynamics produced by each neuron encodes its respective margin of separation from a classification hyperplane whose parameters are encoded by the network population dynamics. We believe that the proposed growth transform neuron model and the underlying geometric framework could serve as an important tool to connect well-established machine learning algorithms like SVMs to neuromorphic principles like spiking, bursting, population encoding, and noise shaping.

Signal-to-noise ratio improvement of swept-tone-generated transient otoacoustic emissions.

In this study, we utilized the swept-tone (ST) deconvolution method for comparing the signal-to-noise ratio (SNR) characteristics of ST otoacoustic emissions (OAE) to conventionally acquired click, or transient-evoked(TE), OAE. We generated a hearing-level equalized (HLeq) ST stimulus based on normative loudness metrics at the different frequencies present in the ST. Due to noise-shaping properties of the ST deconvolution method, we anticipated a theoretical SNR gain of +4.26dB in STOAE compared to TEOAE acquired under comparable settings. This prediction was confirmed by computer simulation. HLeq STOAE and TEOAE were then acquired from each of the 22 ears that were tested at five stimulation levels from 5 to 45dB HL, and analyzed responses in terms of their overall SNR. We found that the overall SNR of the HLeq STOAE responses at stimulation levels at or above 15dB HL was significantly higher than that of TEOAE by an average of +3.6dB. Importantly, this leads to recording quality and time-saving improvements in clinical hearing screenings.

A 2.5 V 109 dB DR ΔΣ ADC for Audio Application

Abstract— A 2.5 V feed-forward second-order delta-sigma modulator for audio application is presented. A 9-level quantizer with a tree-structured dynamic element matching (DEM) was employed to improve the linearity by shaping the distortion resulted from the capacitor mismatch of the feedback digital-to-analog converter (DAC). A chopper stabilization technique (CHS) is used to reduce the flicker noise in the first integrator. The prototype delta-sigma analog-to-digital converter (ADC) implemented in a 65 nm 1P8M CMOS process occupies 0.747 mm 2 and achieves 109.1 dB dynamic range (DR), 85.4 dB signal-to-noise ratio (SNR) in a 24 kHz audio signal bandwidth, while consuming 14.75 mW from a 2.5 V supply. Index Terms —Delta-sigma modulator, feed-forward, dynamic element matching, chopper stabilization I. I NTRODUCTION Recent advances of CMOS technology have enabled the high quality signal processing in the multi-media and communication systems and have resulted in a great demand for the high resolution analog-to-digital converters (ADCs). Among various ADC architectures, the delta-sigma ADC offers high dynamic range by using oversampling and noise shaping properties. Moreover, as it requires only simple and relatively high-tolerance analog components with fast and complex digital signal processing to achieve high resolution, it is very well-suited for the digital CMOS process. The theoretical signal-to-quantization noise ratio (SQNR) of the delta-sigma ADC is given by Eq. (1)

A Neuromorphic Single-Electron Circuit for Noise-Shaping Pulse-Density Modulation

We propose a bio-inspired circuit performing pulse-density modulation with single-electron devices. The proposed circuit consists of three single-electron neuronal units, receiving the same input and are connected to a common output. The output is inhibitorily fedback to the three neuronal circuits through a capacitive coupling. The circuit performance was evaluated through Monte-Carlo based computer simulations. We demonstrated that the proposed circuit possesses noise-shaping characteristics, where signal and noises are separated into low and high frequency bands respectively. This significantly improved the signal-tonoise ratio (SNR) by 4.34 dB in the coupled network, as compared to the uncoupled one. The noise-shaping properties are as a result of i) the inhibitory feedback between the output and the neuronal circuits, and ii) static noises (originating from device fabrication mismatches) and dynamic noises (as a result of thermally induced random tunneling events) introduced into the network.

An Inhibitory Neural-Network Circuit Exhibiting Noise Shaping with Subthreshold MOS Neuron Circuits

We designed subthreshold analog MOS circuits implementing an inhibitory network model that performs noise-shaping pulse-density modulation (PDM) with noisy neural elements, with the aim of developing a possible ultralow-power one-bit analog-to-digital converter. The static and dynamic noises given to the proposed circuits were obtained from device mismatches of current sources (transistors) and externally applied random spike currents, respectively. Through circuit simulations we confirmed that the circuit exhibited noise-shaping properties, and signal-to-noise ratio (SNR) of the network was improved by 7.9 dB compared with that of the uncoupled network as a result of noise shaping.

Applying Spiking Neural Nets to Noise Shaping

In recent years, there has been an increased focus on the mechanics of information transmission in spiking neural networks. Especially the Noise Shaping properties of these networks and their similarity to Delta-Sigma Modulators has received a lot of attention. However, very little of the research done in this area has focused on the effect the weights in these networks have on the Noise Shaping properties and on post-processing of the network output signal. This paper concerns itself with the various modes of network operation and beneficial as well as detrimental effects which the systematic generation of network weights can effect. Also, a method for post-processing of the spiking output signal is introduced, bringing the output signal more in line with conventional Delta-Sigma Modulators. Relevancy of this research to industrial application of neural nets as building blocks of oversampled A/D converters is shown. Also, further points of contention are listed, which must be thoroughly researched to add to the above mentioned applicability of spiking neural nets.

A Noise-Shaped Switching Power Supply Using a Delta–Sigma Modulator

A technique to reduce in-band tones in switch-mode power supplies is described. It takes advantage of the noise-shaping properties of the delta-sigma (/spl Delta//spl Sigma/) modulator to eliminate the spikes normally present in switching power supplies. A framework is introduced for comparing the conventional pulsewidth modulated (PWM) controller and this approach. A buck converter test circuit is constructed that is designed for a PWM controller clocked at 200 kHz and then substituted with a /spl Delta//spl Sigma/ modulator controller clocked at 400 kHz. The RMS noise power of the PWM controller is 14.9 mW compared to the rms noise power for the /spl Delta//spl Sigma/ modulator of 75.85 mW measured in a 2-MHz bandwidth. Although the /spl Delta//spl Sigma/ modulator rms noise power is higher, the noise floor is below the tones seen at the output of the PWM controller. A multibit /spl Delta//spl Sigma/ modulator controller, however, provides a significant reduction in the spectral output of the power supply. Values of 3.75 and 0.24 mW rms noise power are observed at the output of a 2-bit and 4-bit /spl Delta//spl Sigma/ modulator controller, respectively.

Superconducting second-order sigma-delta modulators utilizing multi-flux-quantum generators

We have been developing a superconducting second-order sigma-delta analog-to-digital converter with a large bandwidth and a large dynamic range for software radio applications. In a superconducting second-order sigma-delta modulator utilizing a passive integrator and single-flux-quantum (SFQ) feedback, gain to compensate the large attenuation in the passive integrator of the modulator is required to obtain a large dynamic range. In this paper, a second-order modulator utilizing multi-flux-quantum (MFQ) generators creating the needed gain is reported and the design and experimental test results of the elementary circuits including a comparator, a first-order modulator, and the MFQ generator are described. The digital outputs of the comparator and the first-order modulator were experimentally evaluated, where the input dependence of the comparator switching probability and the noise-shaping properties of the modulator were clearly observed. The low speed operation of the MFQ generator creating three SFQ pulses was experimentally confirmed. The other circuits were also tested at low frequencies.

Delta-sigma oscillators: versatile building blocks

Delta–sigma modulators have long been used in signal-processing applications to simplify arithmetic operations. Their ability to trade bandwidth for quantization levels has been exploited to reduce hardware requirements and speed up computations. This paper will introduce a class of circuits called delta–sigma oscillators which use this property to efficiently generate spectrally pure analogue signals. Subsequently we will show how this approach can be extended to generate various multitone signals such as AM and FM signals. Delta–sigma modulators with various noise-shaping properties are at the core of these new designs. Owing to their small-silicon-area requirements and digital implementation, delta–sigma oscillators have been identified as an important building block for built-in self-test schemes for mixed-signal circuits and systems. They are also envisioned to be useful building blocks for various control and communication system applications. © 1997 by John Wiley & Sons, Ltd.

Frequency domain coding of speech

Frequency domain techniques for speech coding have recently received considerable attention. The basic concept of these methods is to divide the speech into frequency components by a filter bank (sub-band coding), or by a suitable transform (transform coding), and then encode them using adaptive PCM. Three basic factors are involved in the design of these coders: 1) the type of the filter bank or transform, 2) the choice of bit allocation and noise shaping properties involved in bit allocation, and 3) the control of the step-size of the encoders. This paper reviews the basic aspects of the design of these three factors for sub-band and transform coders. Concepts of short-time analysis/synthesis are first discussed and used to establish a basic theoretical framework. It is then shown how practical realizations of subband and transform coding are interpreted within this framework. Principles of spectral estimation and models of speech production and perception are then discussed and used to illustrate how the side information can be most efficiently represented and utilized in the design of the coder (particularly the adaptive transform coder) to control the dynamic bit allocation and quantizer step-sizes. Recent developments and examples of the vocoder-driven adaptive transform coder for low bit-rate applications are then presented.