Digital signal processing

This work presents a novel Anti-Islanding (AI) protection of Photovoltaic (PV) Systems based on monitoring the dc-link voltage of the PV inverter. A PV System equipped with AI protection like frequency relays, a rate of change of frequency (ROCOF) relay, and respectively the proposed dc-link voltage relay is simulated under the conditions of islanding and the detection time for all these AI techniques are compared. The study shows under which conditions our proposed dc-link voltage AI relay is the most efficient.


This work presents a Matlab/Simulink study on anti-islanding detection algorithms for a 100kW Grid-Connected Photovoltaic (PV) Array. The main focus is on the islanding phenomenon that occurs at the Point of Common Coupling (PCC) between Grid-Connected PV System and the rest of the electric power system (EPS) during various grid fault conditions. The Grid-Connected PV System is simulated under the conditions of islanding, and anti-islanding (AI) relay reaction times are measured through the simulation.


This work aims to implement in Matlab and Simulink the perturb-and-observe (P&O) and incremental conductance Maximum Power Point Tracking (MPPT) algorithms that are published in the scientific literature.


This work presents the performance evaluation of incremental conductance maximum power point tracking (MPPT) algorithm for solar photovoltaic (PV) systems under rapidly changing irradiation condition. The simulation model, carried out in Matlab and Simulink, includes the PV solar panel, the dc/dc buck converter and the MPPT controller. This model provides a good evaluation of performance of MPPT control for PV systems.


Costas arrays are permutation matrices that meet the added Costas condition that, when used as a frequency-hop scheme, allow at most one time-and-frequency-offset signal bin to overlap another.  Databases to various orders have been available for many years.  Here we have a database that is far more extensive than any available before it.  A very powerful and easy-to-use Windows utility with a GUI accompanies the database.


The dataset stores a random sampling distribution with cardinality of support of 4,294,967,296 (i.e., two raised to the power of thirty-two). Specifically, the source generator is fixed as a symmetric-key cryptographic function with 64-bit input and 32-bit output. A total of 17,179,869,184 (i.e., two raised to the power of thirty-four) randomly chosen inputs are used to produce the sampling distribution as the dataset. The integer-valued sampling distribution is formatted as 4,294,967,296 (i.e., two raised to the power of thirty-two) entries, and each entry occupies one byte in storage.


HazeRD is an outdoor scene dataset for benchmarking dehazing algorithms. HazeRD contains 10 different scenes based on the architectural biometrics project. For each scene, the ground RGB images, depth maps, and synthesized hazy images following the atmospheric optics are provided; the hazy images come with five different haze level using real life physical parameters. The main features of HazeRD to other dehazing datasets are: HazeRD focuses on outdoor scenes whereas other datasets provide indoor scenes; and, the synthesis is based on real life parameters. 


The dataset contains depth frames collected using Microsoft Kinect v1 in top-view configuration and can be used for fall detection.


The Million Song Dataset is a freely-available collection of audio features and metadata for a million contemporary popular music tracks. Its purposes are:

  • To encourage research on algorithms that scale to commercial sizes
  • To provide a reference dataset for evaluating research
  • As a shortcut alternative to creating a large dataset with APIs (e.g. The Echo Nest's)
  • To help new researchers get started in the MIR field