Leonardo Reyneri

A neuroengineering suite of computational tools for visual prostheses

The cooperation between neuroscience and biomedical engineering gave rise to a recent, but growing research field, known as neuroengineering. We follow its principles to have a system providing basic descriptions of the visual world to the brains cortex. We describe a set of software and hardware tools to interface with neural tissue, in order to transmit visual information encoded into a bioinspired neural-like form. The set is composed of a retina-like encoder, and a platform to optimize electrical stimulation parameters for a multi-electrode implant. The main objective is to progress towards a functional visual neuroprosthesis for the blind.

An integrated hybrid approach to the design of high-performance intelligent controllers

This paper presents a hybrid approach to the development of high-performance real-time intelligent and adaptive controllers for nonlinear plants. Several paradigms derived from cognitive sciences ore considered and analyzed in this work, such as neural networks, fuzzy inference systems, genetic algorithms, etc. Although most of these paradigms are widely known and have been used extensively in the field of automatic control since several years, the novelty of the proposed approach resides in their tight integration and its capability of allowing a hybrid design. The different control strategies have also been integrated with the theory of finite state automata, in such a way that an automaton tracks the different plant states and selects accordingly one out of a given number of controller characteristics, each one being designed in a hybrid manner. State transitions can also be triggered by fuzzy and neural signals. Finally, two practical examples of the proposed hybrid approach are analyzed.

Design, implementation, and thermal modeling of embedded reconfigurable magnetorquer system for nanosatellites

A reconfigurable magnetorquer coil has been designed and implemented for the CubeSat power management, attitude determination, and control tile (CubePMT) module of CubeSat-standard nanosatellites. Magnetorquer coil is a good choice for attitude control and stabilization of nanosatellites. The goal of this work is to provide CubeSat with a magnetorquer coil, which has small dimensions, low weight, and low heat dissipation. The designed magnetorquer coil is reconfigurable and integrated within the printed circuit board internal layers, occupying no extra space on CubeSat. Coils in each layer are treated separately and can be attached and detached through straps. Changing the arrangement of these straps, one can use 1, 2, 3, or 4 coils in series, parallel, or any hybrid combination. This reconfigurable design provides an option for generating different amounts of magnetic moment and resultant torque to stabilize and rotate the satellite. Emissivity of the CubePMT module was found through lab experiments. Power dissipation and the corresponding temperature increase of the CubePMT module are evaluated by thermal modeling.

Evaluation, Classification and Clustering with Neuro-Fuzzy Techniques in Integrate Pest Management

In the present article are described the results obtained by the application of neuro-fuzzy methodologies in the study of Bactrocera Oleae (olive fly) infestation in Liguria region olive grows.The main aim of this project is create an informatic decisional support for experts in the applications of Integrated Pest Management strategies against the Bactrocera Oleae infestation. This system will suggest an appropriate treatments for each monitored farm to optimize the quality of the olive oil and the economic and environmental impact of these treatments.Forecast and statistical analyses on agronomic data sets like the case in study (the growth of olive fly), are actually made using standard approaches like analytical ones; this kind of data are very variable and non-linear, characteristics which make them complex to be treated mathematically. Agronomic research needs to introduce new analysis techniques for taking data and information, for example neuro-fuzzy techniques that allow a large use of infestation data with a good flexibility degree.

Modularity and Reliability in Low Cost AOCSs

Commercial Off The Shelf Components (COTS) are sometimes subject to reliability requirements which are often tougher than those applied to space devices, as they have to be used in markets (e.g., automotive) where safety concerns and the huge number of systems manufactured set demanding constraints on the components. Yet, the drawbacks of COTS components and other low cost design methods, mostly in space missions, remain the higher sensitivity to radiation-induced effects and the reduced system level tolerance to faults.

A Neural Network Chip Using CPWM Modulation

This paper describes a silicon implementation of an Artificial Neural Networks based on Coherent Pulse Width modulation techniques. Synapses use current generators controlled by an input Pulse Stream. Net charge generated is the product of synaptic current by pulse width. Neurons accumulate synaptic contributions and convert internal activation into an output Pulse Stream. A system optimized for lowest computation energy and highest reconfigurability has been designed, manufactured and tested.