Signal Processing

Dataset of V2V (vehicle to vehicle communication), GPS, inertial and WiFi data collected during a road vehicle trip in the city of Porto, Portugal. Four cars were driven along the same route (approx. 12 km), facing everyday traffic conditions with regular driving behavior. No special environments or settings were chosen, other than keeping the vehicles in communication reach of each other for as long as possible while being safe and compliant with the road rules.

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Speech Processing in noisy condition allows researcher to build solutions that work in real world conditions. Environmental noise in Indian conditions are very different from typical noise seen in most western countries. This dataset is a collection of various noises, both indoor and outdoor ollected over a period of several months. The audio files are of the format RIFF (little-endian) data, WAVE audio, Microsoft PCM, 8 bit, mono 11025 Hz and have been recorded using the Dialogic CTI card.

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The endmembers of a hyperspectral image (HSI) are more likely to be generated by independent sources and be mixed in a macroscopic degree before arriving at the sensor element of the imaging spectrometer as mixed spectra.

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Tactile perception of the material properties in real-time using tiny embedded systems is a challenging task and of grave importance for dexterous object manipulation such as robotics, prosthetics and augmented reality [1-4] . As the psychophysical dimensions of the material properties cover a wide range of percepts, embedded tactile perception systems require efficient signal feature extraction and classification techniques to process signals collected by tactile sensors in real-time.

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The training, validation, and test set used for Deep Xi (https://github.com/anicolson/DeepXi). 

 Training set:

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This is the noisy-speech test set used in the original Deep Xi paper: https://doi.org/10.1016/j.specom.2019.06.002. The clean speech and noise used to create the noisy-speech set are also available.

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Noisy-speech set used to test Deep Xi (https://github.com/anicolson/DeepXi). The clean speech and noise used to create the noisy-speech set are also available. The clean-speech recordings are from Librispeech test-clean (http://www.openslr.org/12/).

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558 Views

The dataset consists of two populations of fetuses: 160 healthy and 102 Late Intra Uterine Growth Restricted (IUGR). Late IUGR is an adverse pathological condition encompassing chronic hypoxia as a consequence of placental insufficiency, resulting in an abnormal rate of fetal growth. In standard clinical practice, Late IUGR diagnosis can only be suspected in the third trimester and ultimately confirmed at birth. This data collection comprises of a set of 31 Fetal Heart Rate (FHR) indices computed at different time scales and domains accompanied by the clinical diagnosis.

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The present database contains records of underwater sounds produced by dolphins of the species Tursiops Truncatos. The dolphins live in Dolphinarium Varna (Varna, Bulgaria) and are a family of five

individuals. The records was made in the autumn 2019 by the “SigNautic Lab” crew, using measurement equipment of the world’s leading suppliers Bruel&Kjaer and National Instruments. The database

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2117 Views

BCI-Double-ErrP-Dataset is an EEG dataset recorded while participants used a P300-based BCI speller. This speller uses a P300 post-detection based on Error-related potentials (ErrPs) to detect and correct errors (i.e. when the detected symbol does not match the user’s intention). After the P300 detection, an automatic correction is made when an ErrP is detected (this is called a “Primary ErrP”). The correction proposed by the system is also evaluated, eventually eliciting a “Secondary ErrP” if the correction is wrong.

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