scholarly journals Linear Program Reconstruction in Practice

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Aloni Cohen ◽  
Kobbi Nissim
Keyword(s):  
Gaussian Noise ◽  
Reconstruction Algorithm ◽  
Error Rates ◽  
Linear Program ◽  
Test Environment ◽  
Real Dataset ◽  
Statistical Queries

We briefly report on a successful linear program reconstruction attack performed on a production statistical queries system and using a real dataset. The attack was deployed in test environment in the course of the Aircloak Challenge bug bounty program and is based on the reconstruction algorithm of Dwork, McSherry, and Talwar. We empirically evaluate the effectiveness of the algorithm and a related algorithm by Dinur and Nissim with various dataset sizes, error rates, and numbers of queries in a Gaussian noise setting.

Computed tomography reconstruction on distributed storage using hybrid regularization approach

2019 ◽  
Vol 33 (06) ◽  
pp. 1950063 ◽  
Author(s):  
Shailendra Tiwari ◽  
Kavkirat Kaur ◽  
Yadunath Pathak ◽  
Shivendraa Shivani ◽  
Kuldeep Kaur
Keyword(s):  
Computed Tomography ◽  
Gaussian Noise ◽  
Distributed Storage ◽  
Hybrid Approach ◽  
Computational Cost ◽  
Reconstruction Algorithm ◽  
Noise Robustness ◽  
Projection Data ◽  
Reconstruction Method ◽  
Ct Reconstruction

Computed Tomography (CT) is considered as a significant imaging tool for clinical diagnoses. Due to low-dose radiation in CT, the projection data is highly affected by Gaussian noise which may lead to blurred images, staircase effect, loss of basic fine structure and detailed information. Therefore, there is a demand for an approach that can eliminate noise and can provide high-quality images. To achieve this objective, this paper presents a new statistical image reconstruction method by proposing a suitable regularization approach. The proposed regularization is a hybrid approach of Complex Diffusion and Shock filter as a prior term. To handle the problem of prominent Gaussian noise as well as ill-posedness, the proposed hybrid regularization is further combined with the standard Maximum Likelihood Expectation Maximization (MLEM) reconstruction algorithm in an iterative manner and has been referred to as the proposed CT-Reconstruction (CT-R) algorithm here after. Besides, considering the large sizes of image data sets for medical imaging, distributed storage for images have been employed on Hadoop Distributed File System (HDFS) and the proposed MLEM algorithms have been deployed for improved performance.The proposed method has been evaluated on both the simulated and real test phantoms. The final results are compared with the other standard methods and it is observed that the proposed method has many desirable properties such as better noise robustness, less computational cost and enhanced denoising effect.

scholarly journals Error Rates of M-PAM and M-QAM in Generalized Fading and Generalized Gaussian Noise Environments

2013 ◽  
Vol 17 (10) ◽  
pp. 1932-1935 ◽  
Author(s):  
Hamza Soury ◽  
Ferkan Yilmaz ◽  
Mohamed-Slim Alouini
Keyword(s):  
Gaussian Noise ◽  
Error Rates ◽  
Generalized Gaussian Noise

scholarly journals Szemmozgások elemzése tradicionális és újszerű vizuális tesztkörnyezetben: a háttérkép disztraktor hatása a szakkádikus paraméterekre

2020 ◽  
Vol 75 (3) ◽  
pp. 367-389
Author(s):  
Somoskeöy Szabolcs ◽  
Kovács Ildikó ◽  
Mezei Márton ◽  
Hoffmann Ildikó ◽  
Tóth László ◽  
...  
Keyword(s):  
Healthy Subjects ◽  
Recognition Task ◽  
Test Group ◽  
Error Rates ◽  
International Standards ◽  
Published Data ◽  
Visual Test ◽  
Eye Tracker ◽  
Test Environment ◽  
Direction Error

Háttér és célkitűzésekA szakkádikus szemmozgási paraméterek biomarkerként történő önálló használata egyes degeneratív neuropszhichiátriai kórképek felismerésében egyelőre kérdéses. Jelen vizsgálatunk célkitűzése egy olyan szakkádikus szemmozgásvizsgálati protokoll megvalósítása, amely a nemzetközi klinikai kutatásoknak megfelelően kialakított vizsgálati paraméterekkel jellemezhető. Továbbá egészséges vizsgált személyek szakkádparamétereinek a nemzetközileg publikált adatokkal való összehasonlítása, illetve a Boston Sütilopás feladatban használt kép vizuális tesztkörnyezetbe történő beépítésének disztraktor-hatásvizsgálata a szakkádikus paraméterekre.MódszerVizsgálatainkat egészséges önkéntes alanyokon végeztük Tobii Pro X3-120 berendezéssel, két eltérő vizuális környezetet tartalmazó, egyéb tekintetben teljesen megegyező felépítésű, proszakkád és antiszakkád tesztek gap és overlap feladataiban. Az egyik csoport vizuális tesztkörnyezete standard szürke háttérből és fekete stimulusokból állt (STD tesztcsoport), a másiké a Boston Afázia Teszt Sütilopás képleírási feladatban használt képet és zöld-piros színű stimulusokat tartalmazott (BSL tesztcsoport).EredményekA proszakkád és antiszakkád overlap latencia mindkét csoportban nagyobb volt, mint a gap feladatban. A vizsgálati alanyok életkora közepes erősségű módon korrelált az STD csoport proszakkád gap latenciájával, illetve a BSL csoport proszakkád overlap latencia, antiszakkád gap/overlap latencia és overlap időtartam értékével. A csoportok közötti életkori eltérés statisztikai kontrollja mellett nem találtunk különbséget a proszakkád és antiszakkád latencia, illetve csúcssebesség tekintetében. A szakkád időtartamok szignifi kánsan rövidebbek voltak a BSL csoportban. Az iránytévesztési ráta a proszakkád tesztben megegyezett; az antiszakkád gap időtartam, az overlap időtartam, illetve a gap iránytévesztési ráta szignifi káns csoportkülönbséget mutatott.KövetkeztetésekA nemzetközi sztenderdeknek megfelelő újszerű vizsgálati protokoll alkalmasnak látszik hagyományos neuropszichológiai tesztekkel és kutatócsoportunk közelmúltban kidolgozott automatikus beszédfelismerő algoritmusokat alkalmazó tesztjeivel kombinálva egészséges és demencia szindrómával élő személyek multimodális klinikai vizsgálatában történő felhasználásra.Background and aimsThe use of saccadic parameters as specifi c biomarkers in the diagnosis of degenerative neuropsychiatric disorders is still problematic. The aim of the current study was to 1) establish a protocol for saccadic eye movement measurements that is concordant with international clinical investigations; 2) compare saccadic parameters of healthy subjects with internationally published data, and 3) integrate the picture from Boston Cookie Theft test into the visual test environment and evaluate its distractor effects on saccadic parameters.MethodsHealthy volunteers were assessed with Tobii Pro X3-120 eye tracker in two distinct visual settings, but otherwise identical test environment evaluating prosaccades and antisaccades in gap and overlap conditions. One group was assessed in a visual test environment based on a traditional uniform grey background with black stimuli (STD test group), while the visual test environment of the other group contained the Cookie Theft picture of the Boston Diagnostic Aphasia Examination with green and red stimuli (BSL group).ResultsProsaccade and antisaccade latencies were signifi cantly longer in the overlap condition both in the BSL and STD groups. After controlling for age, the STD and BSL group did not differ in terms of prosaccade latency, antisaccade latency or peak velocity; only saccade durations were shorter in the BSL group. Saccadic direction error rate in the prosaccade task was identical in both groups, while the antisaccade gap duration, overlap duration and gap direction error rates showed signifi cant group differences.The present, newly developed protocol conforms to international standards, and may be useful for multi-modal clinical studies assessing healthy subjects and people suffering from dementia, combined with traditional neuropsychological tasks and the speech recognition task recently developed by our research group.

On the error rates of differentially detected narrowband pi /4-DQPSK in Rayleigh fading and Gaussian noise

1993 ◽  
Vol 42 (3) ◽  
pp. 259-265 ◽  
Author(s):  
C.S. Ng ◽  
T.T. Tjhung ◽  
F. Adachi ◽  
K.M. Lye
Keyword(s):  
Gaussian Noise ◽  
Rayleigh Fading ◽  
Error Rates

Chase-Like Decoding of Arithmetic Codes with Applications

2013 ◽  
pp. 27-41
Author(s):  
Amin Zribi ◽  
Sonia Zaibi ◽  
Ramesh Pyndiah ◽  
Ammar Bouallègue
Keyword(s):  
Image Compression ◽  
Gaussian Noise ◽  
Iterative Decoding ◽  
Convolutional Code ◽  
Additive White Gaussian Noise ◽  
Error Rates ◽  
Sequence Estimation ◽  
Awgn Channel ◽  
Arithmetic Codes ◽  
Classical Arithmetic

Motivated by recent results in Joint Source/Channel (JSC) coding and decoding, this paper addresses the problem of soft input decoding of Arithmetic Codes (AC). A new length-constrained scheme for JSC decoding of these codes is proposed based on the Maximum a posteriori (MAP) sequence estimation criterion. The new decoder, called Chase-like arithmetic decoder is supposed to know the source symbol sequence and the compressed bit-stream lengths. First, Packet Error Rates (PER) in the case of transmission on an Additive White Gaussian Noise (AWGN) channel are investigated. Compared to classical arithmetic decoding, the Chase-like decoder shows significant improvements. Results are provided for Chase-like decoding for image compression and transmission on an AWGN channel. Both lossy and lossless image compression schemes were studied. As a final application, the serial concatenation of an AC with a convolutional code was considered. Iterative decoding, performed between the two decoders showed substantial performance improvement through iterations.

scholarly journals Exploiting general independence criteria for network inference

2017 ◽  
Author(s):  
Petras Verbyla ◽  
Nina Desgranges ◽  
Sylvia Richardson ◽  
Lorenz Wernisch
Keyword(s):  
Gaussian Noise ◽  
Network Inference ◽  
Error Rates ◽  
Fine Tuning ◽  
Functional Dependencies ◽  
Tuning Parameters ◽  
Linear Relationships ◽  
Pc Algorithm ◽  
Distance Covariance ◽  
Non Gaussian

ABSTRACTInference of networks representing dependency relationships is a key tool for understanding data derived from biological systems. It has been shown that nonlinear relationships and non-Gaussian noise aid detection of directions of functional dependencies. In this study we explore how far generalised independence criteria for statistical independence proposed in the literature are better suited to the inference of networks compared to standard independence criteria based on linear relationships and Gaussian noise. We compare such criteria within the framework of the PC algorithm, a popular network inference algorithm for directed acyclic dependency graphs. We also propose and evaluate a method to apply unconditional independence criteria to assess conditional independence and a method to simulate data with desired properties from experimental data. Our main finding is that a recently proposed criterion based on distance covariance performs well compared to other independence criteria in terms of error rates, speed of computation, and need of fine-tuning parameters when applied to experimental biological datasets.

scholarly journals Reinforcement Learning with Perturbed Rewards

2020 ◽  
Vol 34 (04) ◽  
pp. 6202-6209 ◽  
Author(s):  
Jingkang Wang ◽  
Yang Liu ◽  
Bo Li
Keyword(s):  
Reinforcement Learning ◽  
Gaussian Noise ◽  
State Of The Art ◽  
Confusion Matrix ◽  
Error Rates ◽  
Average Score ◽  
Sample Complexity ◽  
Noisy Environments ◽  
The Core ◽  
Made In

Recent studies have shown that reinforcement learning (RL) models are vulnerable in various noisy scenarios. For instance, the observed reward channel is often subject to noise in practice (e.g., when rewards are collected through sensors), and is therefore not credible. In addition, for applications such as robotics, a deep reinforcement learning (DRL) algorithm can be manipulated to produce arbitrary errors by receiving corrupted rewards. In this paper, we consider noisy RL problems with perturbed rewards, which can be approximated with a confusion matrix. We develop a robust RL framework that enables agents to learn in noisy environments where only perturbed rewards are observed. Our solution framework builds on existing RL/DRL algorithms and firstly addresses the biased noisy reward setting without any assumptions on the true distribution (e.g., zero-mean Gaussian noise as made in previous works). The core ideas of our solution include estimating a reward confusion matrix and defining a set of unbiased surrogate rewards. We prove the convergence and sample complexity of our approach. Extensive experiments on different DRL platforms show that trained policies based on our estimated surrogate reward can achieve higher expected rewards, and converge faster than existing baselines. For instance, the state-of-the-art PPO algorithm is able to obtain 84.6% and 80.8% improvements on average score for five Atari games, with error rates as 10% and 30% respectively.

Error Rates for Fading NCFSK Signals in an Additive Mixture of Impulsive and Gaussian Noise

1982 ◽  
Vol 30 (11) ◽  
pp. 2434-2438 ◽  
Author(s):  
L. Izzo ◽  
L. Panico ◽  
L. Paura
Keyword(s):  
Gaussian Noise ◽  
Error Rates

Error Rates in Differentially Coherent Phase Systems in Non-Gaussian Noise

1966 ◽  
Vol 14 (5) ◽  
pp. 594-601 ◽  
Author(s):  
J. Halton ◽  
A. Spaulding
Keyword(s):  
Gaussian Noise ◽  
Error Rates ◽  
Coherent Phase ◽  
Phase Systems ◽  
Non Gaussian
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