Signal Processing

The ADAB database (The Arabic handwriting Data Base) was developed to advance the research and development of Arabic on-line handwritten systems. This database is developed in cooperation between the Institut fuer Nachrichtentechnik (IfN) and Research Groups in Intelligent Machines, University of Sfax, Tunisia. The text written is from 937 Tunisian town/village names. A pre-label assigned to each file consists of the postcode in a sequence of Numeric Character References, which stored in the UPX file format.

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The PD-BioStampRC21 dataset provides data from a wearable sensor
accelerometry study conducted for studying activity, gait, tremor, and
other motor symptoms in individuals with Parkinson's disease (PD).  In
addition to individuals with PD, the dataset also includes data for
controls that also went through the same study protocol as the PD
participants.  Data were acquired using lightweight MC 10 BioStamp RC
sensors (MC 10 Inc, Lexington, MA), five of which were attached to
each participant for gathering data over a roughly two day
interval.

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This data is used to test parameter estimation algorithms of complex exponiential signal with Gaussian White Noise. The data can be used to test RMSE of different SNR, N, and p value.

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This open access webpage has all miscellaneous data and design related to ß-machines- Non-Medical, ß-Biomedical machines, processed ECG, sensors, heart and breathing patterns, sounds, finite element analysis, mathematics and BioEngineering. 

As all only want free download and I used to get emails to share data freely ; with IEEE DataPort I had began journey of Data, so I will do update data as long as IEEE DataPort allows it or as long as I can or . I might also upload same data externally to other site.

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Falls are a major health problem with one in three people over the age of 65 falling each year, oftentimes causing hip fractures, disability, reduced mobility, hospitalization and death. A major limitation in fall detection algorithm development is an absence of real-world falls data. Fall detection algorithms are typically trained on simulated fall data that contain a well-balanced number of examples of falls and activities of daily living. However, real-world falls occur infrequently, making them difficult to capture and causing severe data imbalance.

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This dataset is in support of my following Research papers  

Preprint  (Make sure you have read Caution) :

  • Novel ß Transtibial Prosthetic 9-DoF Artificial Leg Adaptive Controller - Part I* 

  https://doi.org/10.36227/techrxiv.19758517.v1

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This dataset is in support of my Research paper 'Design of 6-DoF Combat Quadcopter'.

Preprint:   

The system is basic, on existing designs.It is very simple for any graduate,degree holder.

 

Related Claim : Novel ß Non-Linear Theory

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This is an open-access page. All content can be freely downloaded after sign-up. This webpage contains datasets and models, which are in support of my Research papers-'Geometrical Insight on Sinusoidal Waveform - Part I and Geometrical Insight on Sinusoidal Waveform - Part II'.  

I have used Python, Julia, MATLAB, Scilab, PSPICE   The known code, modified code and other codes along with

 

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The dataset consists a training and testing folder with received signal strength (RSS) data, obtained from a ray-tracing software (Wireless Insite). There are K=8 anchor nodes and N=12 regions.

- In the folder _training, it contains 8 * 12 = 96 separate .p2m files, each file corresponds to a RSS data collected from a grid number of user locations (coordinate is given in the .p2m file) with respect to a certain Anchor node

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