The Usage of ANN for Regression Analysis in Visible Light Positioning Systems.

In this paper, we study the design aspects of an indoor visible light positioning (VLP) system that uses an artificial neural network (ANN) for positioning estimation by considering a multipath channel. Previous results usually rely on the simplistic line of sight model with limited validity. The study considers the influence of noise as a performance indicator for the comparison between different design approaches.

Performance of Vehicular Visible Light Communications under the Effects of Atmospheric Turbulence with Aperture Averaging.

In this paper, we investigate the performance of a vehicular visible light communications (VVLC) link with a non-collimated and incoherent light source (a light-emitting diode) as the transmitter (Tx), and two different optical receiver (Rx) types (a camera and photodiode (PD)) under atmospheric turbulence (AT) conditions with aperture averaging (AA). First, we present simulation results indicating performance improvements in the signal-to-noise ratio (SNR) under AT with AA with increasing size of the optical concentrator. Experimental investigations demonstrate the potency of AA in mitigating the induced signal fading due to the weak to moderate AT regimes in a VVLC system.

The Utilization of Artificial Neural Network Equalizer in Optical Camera Communications.

In this paper, we propose and validate an artificial neural network-based equalizer for the constant power 4-level pulse amplitude modulation in an optical camera communications system. We introduce new terminology to measure the quality of the communications link in terms of the number of row pixels per symbol Npps, which allows a fair comparison considering the progress made in the development of the current image sensors in terms of the frame rates and the resolutions of each frame. Using the proposed equalizer, we experimentally demonstrate a non-flickering system using a single light-emitting diode (LED) with Npps of 20 and 30 pixels/symbol for the unequalized and equalized systems, respectively.

An Indoor Visible Light Positioning System Using Tilted LEDs with High Accuracy.

The accuracy of the received signal strength-based visible light positioning (VLP) system in indoor applications is constrained by the tilt angles of transmitters (Txs) and receivers as well as multipath reflections. In this paper, for the first time, we show that tilting the Tx can be beneficial in VLP systems considering both line of sight (LoS) and non-line of sight transmission paths. With the Txs oriented towards the center of the receiving plane (i.

Optical Axons for Electro-Optical Neural Networks.

Recently, neuromorphic sensors, which convert analogue signals to spiking frequencies, have ‎been reported for neurorobotics. In bio-inspired systems these sensors are connected to the main neural unit to perform ‎post-processing of the sensor data. The performance of spiking neural networks has been ‎improved using optical synapses, which offer parallel communications between the distanced ‎neural areas but are sensitive to the intensity variations of the optical signal.