Digital signal processing

The dataset contains fundamental approaches regarding modeling individual photovoltaic (PV) solar cells, panels and combines into array and how to use experimental test data as typical curves to generate a mathematical model for a PV solar panel or array.



The work starts with a short overview of grid requirements for photovoltaic (PV) systems and control structures of grid-connected PV power systems. Advanced control strategies for PV power systems are presented next, to enhance the integration of this technology. The aim of this work is to investigate the response of the three-phase PV systems during symmetrical and asymmetrical grid faults.


This dataset contains the synthetic stimuli used in the study published in the paper "A Comparative Study of 3D and 1D Acoustic
Simulations of the Higher Frequencies of Speech". The goal of this study was to evaluate the accuracy of the acoustic wave
propagation in the vocal tract in a source-filter synthesis paradigm with two perceptual experiments. The high frequencies (above 4 kHz) of the stimuli were
generated by three different methods: a source-filter method relying on a 1D and a 3D acoustic model, and a bandwith extension


The "Queue Waiting Time Dataset" is a detailed collection of information that records the movement of waiting times in queues. This dataset contains important details such as the time of arrival, the start and finish times, the waiting time, and the length of the queue. The arrival time denotes the moment when customers enter the queue, while the start and finish times track the duration of the service process. The waiting time measures the time spent waiting in the queue, and the queue length shows the number of customers in the queue when a new customer arrives.


The data set contains raw channel-sounding data of 30 clinically relevant scenarios, captured in the university clinic of Dresden, Germany, and a script to analyze them. The measurement campaign was conducted in five environments:

  • Infirmary (Inf)
  • Emergency Room (ER)
  • Intensive Care Unit (ICU)
  • Hallway (Hall)
  • Elevator (Elev)

The patients were performing various motion sequences:


Specific emitter identification (SEI)  is a promising authentication paradigm in physical layer security (PLS). Despite the significant success of existing SEI schemes, most of them assume that the distributions of the training dataset and the test dataset are consistent. However, in most practical scenarios, when the signal parameters change, the distribution of the samples will changes,  resulting in a significant performance degradation.


The file ExplanationForPaper.m contains the code that draws the figures in "Periodograms and The Method of Averaged Periodograms."  It also produces many, many other, related figures and performs many related calculations.  By reading through the code and running it, the reader will be able to "experience" the mateiral presented in the article.  The reader will also see material related to the additional application discussed at the end of "The method of averaged periodograms" and just before the section "Numerical examples."


The Intel D435i camera is selected to collect the point cloud data of lower limbs,the point cloud data source was 10 subjects including 4 females and 6 males, subjects are informed and voluntary, aged between 23-26 years, with an average age of 24.3 (±1.03) years, height of 172.1 (±6.46) cm, and weight of 71.3 (±9.58 kg.). The subjects were not trained prior to the testThe experimental data from these ten individuals were divided into two parts, half for training the long and short term memory neural network and half for validating the real-time and accuracy of the training model.


This dataset focuses on cooperative spectrum sensing in a cognitive radio network, where multiple secondary users collaborate to detect the presence of a primary user. We introduce multiple cooperative spectrum sensing schemes based on a tree deep neural network architecture, incorporating a one-dimensional convolutional neural network and a long short-term memory network. The primary objective of these schemes is to effectively learn the activity pattern of the primary user.


The large number and scale of natural and man-made disasters have led to an urgent demand for technologies that enhance the safety and efficiency of search and rescue teams. Semi-autonomous rescue robots are beneficial, especially when searching inaccessible terrains, or dangerous environments, such as collapsed infrastructures. For search and rescue missions in degraded visual conditions or non-line of sight scenarios, radar-based approaches may contribute to acquire valuable, and otherwise unavailable information.