Signal Processing

Radar Modulation Recognition of Intra-pulse Overlapping Signals

Existing work on radar modulation recognition is

widely based on the assumption of a single in-pulse signal,

whereas overlapping two pulse signals is an actual situation. This

paper introduces a challenging problem: modulation recognition

of overlapping intra-pulse signals, where the difficulty lies in

the fact that the number of samples grows stepwise with the

permutation of the sub-signals. In this paper, for the first time,

a series of methods for target detection are used to solve this

Categories:: Signal Processing

349 Views

OTBioLab Data

Ten individuals in good health were enlisted to execute 16 distinct movements involving the wrist and fingers in real-time. Before commencing the experimental procedure, explicit consent was obtained from each participant. Participants were informed that they had the option to withdraw from the study at any point during the experimental session. The experimental protocol adhered to the principles outlined in the Declaration of Helsinki and received approval from the local ethics committee at the National University of Sciences and Technology, Islamabad, Pakistan.

Categories:: Artificial Intelligence
Signal Processing
Continuous-time signal processing
Machine Learning
Biomedical and Health Sciences

122 Views

Radar-based hand, arm, and body gestures

For gesture recognition, radar sensors provide a unique alternative to other input devices, such as cameras or motion sensors. They combine a low sensitivity to lighting conditions, an ability to see through surfaces, and user privacy preservation, with a small form factor and low power usage. However, radar signals can be noisy, complex to analyze, and do not transpose from one radar to another.

Categories:: Signal Processing
Sensors

580 Views

A Novel Adaptive Variational Bayesian Filter for Underwater Localization System with Unknown Noise Statistics

These data is state estimation accuracy of the proposed algorithm When the adjust factor is 1

These data includes the position estimation accuracy and velocity estimation accuracy of the algorithm.

The data are explained as follows:

rmse_ckf_1,rmse_ukf_1,rmse_vakf_1,rmse_vakfpr_1,rmse_okf_1 are the position accuracy of the CKF, UKF, the proposed IW_VACKF, VACKF_PR and CKF-TNCM, respectively.

rmse_ckf_2,rmse_ukf_2,rmse_vakf_2,rmse_vakfpr_2,rmse_okf_2 are the velocity accuracy of the CKF, UKF, the proposed IW_VACKF, VACKF_PR and CKF-TNCM, respectively.

Categories:: Signal Processing

72 Views

MUSED-I: "Multi-Gesture Surface Electromyography (sEMG) Dataset for Stroke Rehabilitation”

The published Surface Electromyography (sEMG) dataset was captured under the supervision of trained physiotherapists and doctors at Mayo Hospital Lahore and National University of Sciences & Technology by following two months long experimental protocol.

Categories:: Signal Processing
Machine Learning
Wearable Sensing
Biomedical and Health Sciences
Biophysiological Signals

947 Views

Egyptian Arabic Emotional Dataset (EAED)

EAED is an Egyptian-Arabic emotional speech dataset containing 3,614 audio files. The dataset is a semi-natural one as it was collected from five well-known Egyptian TV series. Each audio file ranged in length from 1 to 8 seconds depending on the completion time of the given sentence.