Incompressibility of Classical Distributions Anshu, Anurag; Leung, Debbie; Touchette, Dave
IEEE transactions on information theory,
2022-March, 2022-3-00, Letnik:
68, Številka:
3
Journal Article
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In blind compression of quantum states, a sender Alice is given a specimen of a quantum state <inline-formula> <tex-math notation="LaTeX">\rho </tex-math></inline-formula> drawn from a known ensemble ...(but without knowing what <inline-formula> <tex-math notation="LaTeX">\rho </tex-math></inline-formula> is), and she transmits sufficient quantum data to a receiver Bob so that he can decode a near perfect specimen of <inline-formula> <tex-math notation="LaTeX">\rho </tex-math></inline-formula>. For many such states drawn iid from the ensemble, the asymptotically achievable rate is the number of qubits required to be transmitted per state. The Holevo information is a lower bound for the achievable rate, and is attained for pure state ensembles, or in the related scenario of entanglement-assisted visible compression of mixed states wherein Alice knows what state is drawn. In this paper, we prove a general and robust lower bound on the achievable rate for ensembles of classical states, which holds even in the least demanding setting when Alice and Bob share free entanglement and a constant per-copy error is allowed. We apply the bound to a specific ensemble of only two states and prove a near-maximal separation (saturating the dimension bound in leading order) between the best achievable rate and the Holevo information for constant error. This also implies that the ensemble is incompressible - compression does not reduce the communication cost by much. Since the states are classical , the observed incompressibility is not fundamentally quantum mechanical. We lower bound the difference between the achievable rate and the Holevo information in terms of quantitative limitations to clone the specimen or to distinguish the two classical states.
Magnetically Suspended Control and Sensitive Gyro (MSCSG) is an attitude measurement and attitude control instrument. In order to realize high precision measurement of attitude angle velocity of ...spacecraft under the condition of output torque, a method of magnetically suspended rotor tilt modulation is proposed based on MSCSG. In the paper, the attitude angular velocity measurement principle of MSCSG is analyzed, and a conclusion is drawn that there is a contradiction between the output torque and the measurement accuracy. According to the working characteristics of MSCSG, the tilt modulation method of magnetically suspended rotor is proposed. By actively controlling the angular momentum tilt of the rotor, the method can measure the attitude angular velocity under the condition of output torque. By analyzing the measurement error, the method can effectively compensate the constant error and improve the measurement accuracy of attitude angular velocity. The experimental results show that tilt modulation can improve the measurement accuracy of attitude angle rate by 10 times compared with no tilt modulation. Simulation and experiment verify the correctness and superiority of the proposed method. The proposed method provides theoretical support for the integration of MSCSG attitude measurement and control.
STUDY DESIGN.Systematic review with meta-analysis.
OBJECTIVE.To examine the association between proprioception and pain and disability in people with non-specific low back pain (NSLBP) and the impact ...of potential moderators on the strength of the association.
SUMMARY OF BACKGROUND DATA.NSLBP is a common musculoskeletal disorder and a leading cause of disability. Proprioception deficit has been associated with low back pain and correlated with pain and disability; however, the correlation coefficients presented are conflicting.
METHODS.Systematic literature search was performed in eight databases and Google scholar. Two independent reviewers assessed the literature and extracted data. Data of interest included participant characteristics of NSLBP group, pain and disability, proprioception test protocol, and the correlation coefficient between proprioception and pain/disability. Meta-analysis of data from homogeneous studies was performed according to proprioception test methods. Subgroup of movement directions was analyzed. The methodological quality of studies was assessed.
RESULTS.The literature search identified 3067 records of which 14 studies were included for meta-analysis. Proprioception was measured by active joint repositioning sense (AJRS), passive joint repositioning sense (PJRS), and threshold to detect passive motion (TTDPM). Meta-analysis revealed no significant correlation coefficient between any proprioception measures and pain or disability (P > 0.05). The subgroup analysis showed little correlation between absolute error (AE) of passive lumbar flexion and pain (r = 0.225, 95% CI 0.040–0.395), and between AE of passive lumbar extension and disability (r = 0.196, 95%CI 0.010–0.369).
CONCLUSION.AJRS and TTDPM are not correlated with pain and disability in people with NSLBP. The AE of passive lumbar movement is correlated to a small degree with pain and disability. However, the degree of correlation is small and should be interpreted with caution. Therefore, the differences in proprioception observed between people with pain and people without pain seem to be independent of the symptoms.Level of Evidence1
Online handwritten word recognition (OHR) in low-resource languages such as Bangla is still an open problem. Although the need and importance of OHR are increasing nowadays, research works on ...word-level recognition are few (specifically for Bangla script), and there is a lot of room for improving recognition performance. In the current work, we employed different Recurrent Neural Network (RNN) architectures such as Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BLSTM), Gated Recurrent Unit (GRU), and Bidirectional Gated Recurrent Unit (BGRU) for the recognition of online handwritten Bangla words written in an unconstrained domain. One of the challenges includes the variable number of strokes used to write words. This study aims to develop a segmentation-free recognition module where the features from constituent strokes of the word sample are fed to the developed RNN architectures. Sequential and dynamic information obtained from the strokes is considered as the features for the current experiment. The customized architecture of BLSTM known as
BWordDeepNet
(Bangla Word Deep-learning Network) provides the best performance with 98.35% correct recognition accuracy on the dataset having 7992 online handwritten Bangla word samples. Additionally, the model achieves a numerical gain of 8.08% compared to the Bangla word recognition work mentioned in
38
that was performed on the same word dataset containing 5550 word samples. We have also compared the performance of our proposed model with state-of-the-art techniques used for the same purpose.
Tracking is a process of finding continuous path of a selected target. Tracking is important in various civil and defense applications. For tracking applications, various adaptive filters are being ...used such as Kalman Filter and it's variants. In this paper, a popular meta-heuristic algorithm, namely, Particle Swarm Optimization (PSO) algorithm is applied to track a target which is a robot and it is transmitting noisy data due to installation of cheap quality sensors onboard. These noisy observations are filtered by PSO algorithm in order to estimate true path of the robot. The simulated results are presented by using MATLAB software. From the results, it is observed that the PSO algorithm is very effective algorithm in estimating the target location continuously with almost zero estimation error. Thus, Particle Swarm Optimization algorithm is a suitable algorithm for robot tracking applications and it can also be used for nonlinear data processing in autonomous robot design applications.
A new sensorless control algorithm for brushless dc motors (BLDCMs) is proposed in this paper. The torque constant of a BLDCM is used as a reference signal for position detection because it is ...constant during the entire speed range and can be estimated by calculating the ratio of the back electromotive force (EMF) to the rotor speed. By using both a disturbance observer and the torque constant estimation error, the rotor speed can be obtained. The back EMF can be easily obtained from the voltage equation of the BLDCM. The estimated back EMF decreases simultaneously with the estimated torque constant at the commutation point. By using this phenomenon, the commutation of the phase currents can be done automatically at the drop point of the estimated torque constant. Unlike conventional back-EMF-based methods, the proposed method provides highly accurate sensorless operation even under low speeds because only the drop of the torque constant is used for position detection and current commutation. Therefore, the position accuracy is not affected by the electric parameter errors of the BLDCM. Also, this algorithm does not require an additional hardware circuit for position detection. The validity of the proposed algorithm is verified through several experiments.
According to dominant theories of motor control, speed and accuracy are optimized when, on the average, movement endpoints are located at the target center and when the variability of the movement ...endpoint distributions is matched to the width of the target (viz., Meyer, Abrams, Kornblum, Wright, & Smith, 1988). The current study tested those predictions. According to the speed-accuracy trade-off, expanding the range of variability to the amount permitted by the limits of the target boundaries allows for maximization of movement speed while centering the distribution on the target center prevents movement errors that would have occurred had the distribution been off center. Here, participants (N=20) were required to generate 100 consecutive targeted hand movements under each of 15 unique conditions: There were three movement amplitude requirements (80, 160, 320mm) and within each there were five target widths (5, 10, 20, 40, 80mm). According to the results, it was only at the smaller target widths (5, 10mm) that movement endpoint distributions were centered on the target center and the range of movement endpoint variability matched the range specified by the target boundaries. As target width increased (20, 40, 80mm), participants increasingly undershot the target center and the range of movement endpoint variability increasingly underestimated the variability permitted by the target region. The degree of target center undershooting was strongly predicted by the difference between the size of the target and the amount of movement endpoint variability, i.e., the amount of unused space in the target. The results suggest that participants have precise knowledge of their variability relative to that permitted by the target, and they use that knowledge to systematically reduce the travel distance to targets. The reduction in travel distance across the larger target widths might have resulted in greater cost savings than those associated with increases in speed.
•As target width increased, mean endpoint location undershot the target center.•As target width increased, endpoint variability underestimated the permitted variability.•Amount of unoccupied target space predicts amount of target center undershooting.
Onsets of acoustic stimuli are salient transients and are relevant in humans for the perception of music and speech. Previous studies of onset-duration discrimination and matching focused on whether ...onsets are perceived categorically. In this study, we address two issues. First, we revisit onset-duration matching and measure, for 79 conditions, how accurately and precisely human listeners can adjust the onset duration of a comparison stimulus to subjectively match that of a standard stimulus. Second, we explore measures for quantifying performance in this and other matching tasks. The conventional measures of accuracy and precision are defined by arithmetic descriptive statistics and the Euclidean distance function on the real numbers. We propose novel measures based on geometric descriptive statistics and the log-ratio distance function, the Euclidean distance function on the positive-real numbers. Only these properly account for the fact that the magnitude of onset durations, like the magnitudes of most physical quantities, can attain only positive real values. The conventional (arithmetic) measures possess a convexity bias that yields errors that grow with the width of the distribution of matches. This convexity bias leads to misrepresentations of the constant error and could even imply the existence of perceptual illusions where none exist. This is not so for the proposed (geometric) measures. We collected up to 68 matches from a given listener for each condition (about 34,000 matches in total) and examined inter-listener variability and the effects of onset duration, plateau duration, sound level, carrier, and restriction of the range of adjustable comparison stimuli on measures of accuracy and precision. Results obtained with the conventional measures generally agree with those reported in the literature. The variance across listeners is highly heterogeneous for the conventional measures but is homogeneous for the proposed measures. Furthermore, the proposed measures show that listeners tend to under- rather than to overestimate the onset duration of the comparison stimuli. They further reveal effects of the stimulus carrier on accuracy and precision which are missed by the conventional measures. Our results have broad implications for psychophysical studies that use arithmetic measures to quantify performance when geometric measures should instead be used.
Unconstrained face identification, facial periocular recognition, facial land marking and pose prediction, facial expression recognition, 3D facial model design, and other facial-related problems ...require robust face detection in the wild. Despite the fact that the face recognition issue has been researched intensively for decades with different commercial implementations, it nevertheless faces problems in certain real-world scenarios due to multiple obstacles, such as severe facial occlusions, incredibly low resolutions, intense lighting, exceptionally pose inconsistencies, picture or video compression artefacts, and so on. To solve the problems described above, a face detection technique called Convolution Neural Network with Constant Error Carousel dependent Long Short Term Memory (CNN-CEC-LSTM) is proposed in this paper. This research implemented a novel network structure and designed a special feature extraction that employs a self-channel attention (SCA) block and a self-spatial attention (SSA) block that adaptively aggregates the feature maps in both channel and spatial domains to learn the inter-channel and inter-spatial connection matrices; additionally, matrix multiplications are conducted for a This approach first smoothed the initial image with a Gaussian filter before measuring the gradient image. The Canny-Kirsch Method edge detection algorithm was then used to identify human face edges. The proposed method is evaluated against two recent difficult face detection databases, including the IIT Kanpur Dataset. The experimental findings indicate that the proposed approach outperforms the most current cutting-edge face recognition approaches.
Visuomotor deficits in parietal patients suffering from Optic Ataxia (OA) have been so far studied during natural reaching movements. We aimed at understanding if these disorders are also present ...when more abstract visuomotor transformations are involved. A patient with unilateral OA was tested during both standard reaches and isometric actions, therefore in the absence of hand displacement. Isometric action was affected similarly to standard reaches, with endpoint errors to visual targets that were found in both central and peripheral vision. The dissociation of perceptual and motor components of errors highlighted the existence of field, hand and hemispace effects, which depended on the type of error investigated. A generalization of the reaching disorder to learned isometric conditions would suggest that lesions of posterior parietal cortex (PPC) affect sensory-motor transformations not only for standard reaches, but also when visual signals need to be aligned with information from hand force receptors, therefore regardless of the specific remapping required to generate the directional motor output. The isometric impairment emerged with high and similar severity regardless of whether targets were in central or peripheral vision. Since under all isometric conditions gaze and hand position were decoupled, the spatial correspondence between the hand and the gaze seems to play a critical role in this syndrome. This indicates that regardless of the action to be performed and the specific remapping required, there exists in PPC an abstract representation of the directional motor output, where the computation of eye–hand alignment by parietal neurons plays a crucial role.
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•A patient with unilateral Optic Ataxia (OA) was tested during isometric actions.•OA appears to generalize to isometric actions, both in central and peripheral vision.•The existence of field and hand effects depends on the type of error investigated.•OA is more severe when gaze and hand position are decoupled.
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