Noise Tolerant Research Articles

Investigation of commonly used aortic aneurysm growth rate metrics: Comparing their suitability for clinical and research applications.

An aneurysm is a pathological widening of a blood vessel. Aneurysms of the aorta are often asymptomatic until they rupture, killing approximately 10,000 Americans per year. Fortunately, rupture can be prevented through early detection and surgical repair. However, surgical risk outweighs rupture risk for small aortic aneurysms, necessitating a policy of surveillance. Understanding the growth rate of aneurysms is essential for determining appropriate surveillance windows. Further, identifying risk factors for fast growth can help identify potential interventions. However, studies in the literature have applied many different methods for defining the growth rate of abdominal aortic aneurysms. It is unclear which of these methods is most accurate and clinically meaningful, and whether these heterogeneous methodologies may have contributed to the varied results reported in the literature. To help future researchers best plan their studies and to help clinicians interpret existing studies, we compared five different models of aneurysmal growth rate. We examined their noise tolerance, temporal bias, predictive accuracy, and statistical power to detect risk factors. We found that hierarchical mixed effects models were more noise tolerant than traditional, unpooled models. We also found that linear models were sensitive to temporal bias, assigning lower growth rates to aneurysms that were detected earlier in their course. Our exponential mixed model was noise-tolerant, resistant to temporal bias, and detected the greatest number of clinical risk factors. We conclude that exponential mixed models may be optimal for large studies. Because our results suggest that choice of method can materially impact a study's findings, we recommend that future studies clearly state the method used and demonstrate its appropriateness.

Probing coherence and noise tolerance in discrete-time quantum walks: Unveiling self-focusing and breathing dynamics

The sensitivity of quantum systems to external disturbances is a fundamental problem for the implementation of functional quantum devices, quantum information, and computation. Based on remarkable experimental progress in optics and ultracold gases, we study the consequences of a short-time (instantaneous) noise while an intensity-dependent phase acquisition is associated with a qubit propagating on an $N$ cycle. By employing quantum coherence measures, we report emerging unstable regimes in which quantum walks arise, such as self-focusing and breathing dynamics. Our numerical and analytical results unveil appropriate settings which favor the stable regime, with the asymptotic distribution surviving for weak nonlinearities and disappearing in the thermodynamic limit with $1/N$. The diagram showing the threshold between different regimes reveals the quantum gates close to Pauli-Z as more noise tolerant. As we move towards the Pauli-X quantum gate, such aptness dramatically decreases and the threshold to the self-focusing regime becomes almost unavoidable. Quantum gates close to Hadamard exhibit an unusual aspect, in which an increment of the nonlinear strength can remove the dynamics from the self-focusing regime.

A Noise Tolerant Spread Spectrum Sound-Based Local Positioning System for Operating a Quadcopter in a Greenhouse.

Quadcopters are beginning to play an important role in precision agriculture. In order to localize and operate the quadcopter automatically in complex agricultural settings, such as a greenhouse, a robust positioning system is needed. In previous research, we developed a spread spectrum sound-based local positioning system (SSSLPS) with a 20 mm accuracy within a 30 × 30 m greenhouse area. In this research, a noise tolerant SSSLPS was developed and evaluated. First, the acoustic noise spectrum emitted by the quadcopter was documented, and then the noise tolerance properties of SSSounds were examined and tested. This was done in a greenhouse with a fixed quadcopter (9.75 N thrust) with the positioning system mounted on it. The recorded quadcopter noise had a broadband noise compared to the SSSound. Taking these SSSound properties into account, the noise tolerance of the SSSLPS was improved, achieving a positioning accuracy of 23.2 mm and 31.6 mm accuracy within 12 × 6 m for both Time-division Multiple Access (TDMA) and Frequency-division Multiple Access (FDMA) modulation. The results demonstrate that the SSSLPS is an accurate, robust positioning system that is noise tolerant and can used for quadcopter operation even within a small greenhouse.

A new cryptographic primitive for noise tolerant template security

We introduce a new cryptographic primitive for noise tolerant template security. Our primitive consists of two algorithms. The first algorithm extracts a noise tolerant and secure template of fixed length binary data. The noise tolerance of our scheme follows from the second algorithm that determines whether two templates originate from a pair of data where the Hamming distance belongs to a priori-fixed error tolerance interval. The proposed scheme does not require any encryption infrastructure and its security does not rely on the secrecy of parameters. We discuss the security of our scheme with respect to the irreversibility and indistinguishability of templates and present concrete efficiency and security analysis for practical parameters under certain assumptions. Our techniques can potentially be used to increase security of systems and privacy of users in certain applications including biometric authentication systems and embedded security systems based on Physically Unclonable Functions.

Comparison of Low-Rate Speech Transcoders in Electronic Warfare Situations: Ambe-3000 to G.711, G.726, CVSD

efforts are active to reduce the bit rates but maintaining channel noise tolerance, secure transmission and justified MOS(mean opinion score) among various communication networks. These networks at their end- terminals may employ variety of vocoders operating at different individual bit rates. In order to maintain fidelity, transcoders are used to map the information when traffic flows from one channel operating at one bit rate to another channel operating on another bit rate as seen in the case of channels with different capacities. Some networks (like satellite communication and some private networks) employs codecs like AMBE (Advanced Multiband Excitation), CVSD for their very low bit rate, channel noise tolerant attributes and another features. In order to interface networks accompanying the said vocoders with that of public networks containing codec like PCM, ADPCM, we have done feasibility study for justified MOS using AMBE-3000 HDK. Also, we have compared Transcoders against MOS.

Normally Off ECG SoC With Non-Volatile MCU and Noise Tolerant Heartbeat Detector.

This paper describes an electrocardiograph (ECG) monitoring SoC using a non-volatile MCU (NVMCU) and a noise-tolerant instantaneous heartbeat detector. The novelty of this work is the combination of the non-volatile MCU for normally off computing and a noise-tolerant-QRS (heartbeat) detector to achieve both low-power and noise tolerance. To minimize the stand-by current of MCU, a non-volatile flip-flop and a 6T-4C NVRAM are used. Proposed plate-line charge-share and bit-line non-precharge techniques also contribute to mitigate the active power overhead of 6T-4C NVRAM. The proposed accurate heartbeat detector uses coarse-fine autocorrelation and a template matching technique. Accurate heartbeat detection also contributes system-level power reduction because the active ratio of ADC and digital block can be reduced using heartbeat prediction. Measurement results show that the fully integrated ECG-SoC consumes 6.14 μ A including 1.28- μA non-volatile MCU and 0.7- μA heartbeat detector.

Timing Optimization and Noise Tolerance Dynamic CMOS Logic Design

CMOS logic circuits are used in high performance VLSI chips in order to achieve very high system performance. These circuits requireless number of transistors as compare to CMOS logic circuits. But they suffer from limitations such as noise tolerance, charge leakage, and power consumption. This noise induce in circuits will affect the performance of dynamic circuits. The our work base on noise of MOSFET in contrast to the conventional method which measures drain current noise of MOSFET and divides it by MOSFET transconductance. Therefore, the need for accurate measurement of I-V characteristics of the MOSFET is eliminated, leading to the better accuracy of the measured noise. To design a noise tolerable circuit using dynamic CMOS logic, a new noise tolerant technique is proposed here and then with the help of software we perform parametric analysis to improve the parameters such as noise margin, worst case delay, delayuncertainty, delay sensitivity from their initial performances. By studying those effects we try to put such parameters which help us to make a noise tolerable circuit. Index terms Dynamic Logic Structure, Charge sharing, Keeper logic

Reliable ultra-low-voltage low-power probabilistic-based noise-tolerant latch design

In this paper, we proposed a reliable ultra-low-voltage low-power latch design based on the probabilistic-based Markov random field (MRF) theory [1–3] to greatly improve the ability of noise-tolerance. Through MRF mapping decomposition, we map the previous state and the current state compatible logic function of the latch into the MRF network separately. In this way, we can overcome the challenge of applying Markov random field theory to sequential noise-tolerant circuits. In order to further lower the hardware cost and circuit complexity of the chip, we apply the absorption law and H-tree logic combination techniques [4] to simplify the circuit complexity of the MRF noise-tolerant latch circuit. To preserve the noise tolerant capability of MRF latch, we utilize the cross-coupled latching mechanism in the output of MRF latch. Finally, we apply the proposed MRF latch design in a 16-bit carry-lookahead adder circuit. In TSMC 90nm CMOS process, our proposed circuit can operate reliably under a lower supply voltage of 0.55V with superior noise tolerance and consumes only 31μW power, which is 59.2% lower as compared with the conventional CMOS latch design.

Mining breast cancer genes with a network based noise-tolerant approach

BackgroundMining novel breast cancer genes is an important task in breast cancer research. Many approaches prioritize candidate genes based on their similarity to known cancer genes, usually by integrating multiple data sources. However, different types of data often contain varying degrees of noise. For effective data integration, it’s important to design methods that work robustly with respect to noise.ResultsGene Ontology (GO) annotations were often utilized in cancer gene mining works. However, the vast majority of GO annotations were computationally derived, thus not completely accurate. A set of genes annotated with breast cancer enriched GO terms was adopted here as a set of source data with realistic noise. A novel noise tolerant approach was proposed to rank candidate breast cancer genes using noisy source data within the framework of a comprehensive human Protein-Protein Interaction (PPI) network. Performance of the proposed method was quantitatively evaluated by comparing it with the more established random walk approach. Results showed that the proposed method exhibited better performance in ranking known breast cancer genes and higher robustness against data noise than the random walk approach. When noise started to increase, the proposed method was able to maintained relatively stable performance, while the random walk approach showed drastic performance decline; when noise increased to a large extent, the proposed method was still able to achieve better performance than random walk did.ConclusionsA novel noise tolerant method was proposed to mine breast cancer genes. Compared to the well established random walk approach, it showed better performance in correctly ranking cancer genes and worked robustly with respect to noise within source data. To the best of our knowledge, it’s the first such effort to quantitatively analyze noise tolerance between different breast cancer gene mining methods. The sorted gene list can be valuable for breast cancer research. The proposed quantitative noise analysis method may also prove useful for other data integration efforts. It is hoped that the current work can lead to more discussions about influence of data noise on different computational methods for mining disease genes.

Noise Tolerance Under Risk Minimization

In this paper, we explore noise-tolerant learning of classifiers. We formulate the problem as follows. We assume that there is an unobservable training set that is noise free. The actual training set given to the learning algorithm is obtained from this ideal data set by corrupting the class label of each example. The probability that the class label of an example is corrupted is a function of the feature vector of the example. This would account for most kinds of noisy data one encounters in practice. We say that a learning method is noise tolerant if the classifiers learnt with noise-free data and with noisy data, both have the same classification accuracy on the noise-free data. In this paper, we analyze the noise-tolerance properties of risk minimization (under different loss functions). We show that risk minimization under 0-1 loss function has impressive noise-tolerance properties and that under squared error loss is tolerant only to uniform noise; risk minimization under other loss functions is not noise tolerant. We conclude this paper with some discussion on the implications of these theoretical results.

Noise in interconecction lines for submicrometer CMOS integrated circuits

The growing use of high performance portable systems is the main driving force for the significant advance in the technology of VLSI-CMOS integrated circuits. This advance has been carried out through scaling the transistor and interconnection sizes. However, as the transistor's size and interconnections are getting smaller, the signal integrity is becoming a critical issue. Therefore it is required to develop noise tolerant design circuit techniques in order to enhance the noise tolerance. In addition, these techniques should have a minimum impact on the circuit performance. In this paper, the noise immunity of dynamic logical circuits as the technology scales down is analyzed by using a reliable scaling scenario, and a new noise tolerant design technique is proposed. Prototype circuits implementing the proposed technique have been designed and fabricated. A one-bit carry look-ahead adder was designed using 0.35 mm CMOS-AMS technology. The experimental results show that the design technique here presented, results in an improvement of the ANTE by a factor of 3.4X when compared with the conventional TSPC, and an improvement by a factor of 1.7X when compared with the best noise tolerant technique currently published.

10.1162/153244304773936072

We describe a new boosting algorithm which generates only smooth distributions which do not assign too much weight to any single example. We show that this new boosting algorithm can be used to construct efficient PAC learning algorithms which tolerate relatively high rates of malicious noise. In particular, we use the new smooth boosting algorithm to construct malicious noise tolerant versions of the PAC-model p-norm linear threshold learning algorithms described by Servedio (2002). The bounds on sample complexity and malicious noise tolerance of these new PAC algorithms closely correspond to known bounds for the online p-norm algorithms of Grove, Littlestone and Schuurmans (1997) and Gentile and Littlestone (1999). As special cases of our new algorithms we obtain linear threshold learning algorithms which match the sample complexity and malicious noise tolerance of the online Perceptron and Winnow algorithms. Our analysis reveals an interesting connection between boosting and noise tolerance in the PAC setting.

Learning affine transformations

Under the assumption of weak perspective, two views of the same planar object are related through an affine transformation. In this paper, we consider the problem of training a simple neural network to learn to predict the parameters of the affine transformation. Although the proposed scheme has similarities with other neural network schemes, its practical advantages are more profound. First of all, the views used to train the neural network are not obtained by taking pictures of the object from different viewpoints. Instead, the training views are obtained by sampling the space of affine transformed views of the object. This space is constructed using a single view of the object. Fundamental to this procedure is a methodology, based on singular-value decomposition (SVD) and interval arithmetic (IA), for estimating the ranges of values that the parameters of affine transformation can assume. Second, the accuracy of the proposed scheme is very close to that of a traditional least squares approach with slightly better space and time requirements. A front-end stage to the neural network, based on principal components analysis (PCA), shows to increase its noise tolerance dramatically and also to guides us in deciding how many training views are necessary in order for the network to learn a good, noise tolerant, mapping. The proposed approach has been tested using both artificial and real data.

Discrete orthogonal polynomial deconvolution for time-varying systems

Discrete orthogonal polynomial deconvolution (DOPD) has been demonstrated to be a robust method for obtaining the inverse solution for time-invariant systems. In this communication, extension of the method to time-varying linear systems is explored. The operator-based nature of DOPD lends itself to application to linear time-varying systems expressible as an operator matrix. The stability and noise tolerance characteristics of time-invariant DOPD are demonstrated to apply to tine-varying systems. A priori estimation of the quality of the inverse solution is possible if the characteristics of noise in the forward solution can be estimated. For time-varying linear systems having a region of basis function support approximately congruent to the support region of the transfer function, and for which there is sufficient a priori knowledge of the system, DOPD provides an efficient and noise tolerant method of inverse solution. >