Bioinspired engineering of exploration systems for NASA and DoD

A new approach called bioinspired engineering of exploration systems (BEES) and its value for solving pressing NASA and DoD needs are described. Insects (for example honeybees and dragonflies) cope remarkably well with their world, despite possessing a brain containing less than 0.01% as many neurons as the human brain. Although most insects have immobile eyes with fixed focus optics and lack stereo vision, they use a number of ingenious, computationally simple strategies for perceiving their world in three dimensions and navigating successfully within it. We are distilling selected insect-inspired strategies to obtain novel solutions for navigation, hazard avoidance, altitude hold, stable flight, terrain following, and gentle deployment of payload. Such functionality provides potential solutions for future autonomous robotic space and planetary explorers. A BEES approach to developing lightweight low-power autonomous flight systems should be useful for flight control of such biomorphic flyers for both NASA and DoD needs. Recent biological studies of mammalian retinas confirm that representations of multiple features of the visual world are systematically parsed and processed in parallel. Features are mapped to a stack of cellular strata within the retina. Each of these representations can be efficiently modeled in semiconductor cellular nonlinear network (CNN) chips. We describe recent breakthroughs in exploring the feasibility of the unique blending of insect strategies of navigation with mammalian visual search, pattern recognition, and image understanding into hybrid biomorphic flyers for future planetary and terrestrial applications. We describe a few future mission scenarios for Mars exploration, uniquely enabled by these newly developed biomorphic flyers

Exploration of spatial-temporal dynamic phenomena in a 32×32-cell stored program two-layer CNN universal machine chip prototype

This paper describes a full-custom mixed-signal chip that embeds digitally programmable analog parallel processing and distributed image memory on a common silicon substrate. The chip was designed and fabricated in a standard 0.5 μm CMOS technology and contains approximately 500 000 transistors. It consists of 1024 processing units arranged into a 32 × 32 grid. Each processing element contains two coupled CNN cores, thus, constituting two parallel layers of 32 × 32 nodes. The functional features of the chip are in accordance with the 2nd Order Complex Cell CNN-UM architecture. It is composed of two CNN layers with programmable inter- and intra-layer connections between cells. Other features are: cellular, spatial-invariant array architecture; randomly selectable memory of instructions; random storage and retrieval of intermediate images. The chip is capable of completing algorithmic image processing tasks controlled by the user-selected stored instructions. The internal analog circuitry is designed to operate with 7-bits equivalent accuracy. The physical implementation of a CNN containing second order cells allows real-time experiments of complex dynamics and active wave phenomena. Such well-known phenomena from the reaction-diffusion equations are traveling waves, autowaves, and spiral-waves. All of these active waves are demonstrated on-chip. Moreover this chip was specifically designed to be suitable for the computation of biologically inspired retina models. These computational experiments have been carried out in a developmental environment designed for testing and programming the analogic (analog-and-logic) programmable array processors.Hungarian Academy of Sciences SIVA-2Comisión Interministerial de Ciencia y Tecnología TICC99-0826Office of Naval Research (USA) N00014-00-1-042

Látásjavító implantátumok látóhártya-degenerációkban = Vision restoration with implants in retinal degenerations

Az ideghártya fényérzékelő sejtjeinek maradandó károsodásával járó és vaksághoz vezető betegségek eddig gyógyíthatatlannak bizonyultak. Jelenleg a szembe ültethető retinaimplantátumok fejlesztése biztat leghamarabb a klinikai gyakorlatba is bevezethető eredménnyel e betegek számára. A közlemény célja az eltérő működési elv alapján csoportosított, különböző fejlesztési szakaszban levő implantátumokkal kapcsolatos kutatások ismertetése és jellemzőinek kiemelése, valamint a fejlesztések hazai vonatkozásainak bemutatása. Az összefoglaló a nemzetközi szakirodalomban megjelent publikációk áttekintésével és feldolgozásával, valamint személyes tapasztalatok alapján kíván áttekintést nyújtani a retina degeneratív betegségei esetén beültethető retinaimplantátumokról. Az elmúlt évek mikroelektronikai fejlesztései tették lehetővé, hogy a retina elpusztult fotoreceptorainak helyettesítése elektromos ingerléssel sikeresen megoldható legyen. Több egymástól mind felépítésében, mind egyéb tulajdonságaiban jelentősen eltérő implantátum fejlesztése folyik jelenleg is egymással párhuzamosan. Ezek közül két, az ideghártyával közvetlen kapcsolatban álló, a szemgolyóba ültethető rendszer emelkedik ki. Az ideghártya alá ültethető, subretinalis típusú implantátumokkal sikerült eddig a legfinomabb felbontást elérni. Az ideghártya felszínére rögzített implantátumnak ugyan csekélyebb a felbontása, de rövidebb műtétet igényel a beültetése. A retinaimplantátumok segítségével egyes ideghártya-betegségekben immár bizonyított, hogy látásszerű élmény váltható ki. A multicentrikus klinikai vizsgálatok lezárását követően néhány éven belül várható, hogy többfajta implantátumtípus is megjelenik a klinikai gyakorlatban. Orv. Hetil., 2011, 152, 537–545. | Up until now there has been no available treatment for diseases causing the permanent impairment of retinal photoreceptors. Currently the development of the retinal prostheses is the earliest to promise a result that can be implemented in the clinical treatment of these patients. Implants with different operating principles and in various stages of progress are presented in details, highlighting the characteristics, as well as the Hungarian aspects of the development. This survey intends to provide an overview on retinal prostheses, implantable in case of degenerative diseases of the retina, by reviewing and assessing the papers published in relevant journals and based on personal experience. Developments in microelectronics in recent years made it possible and proved to be feasible to replace the degenerated elements in the retina with electrical stimulation. Multiple comparable approaches are running simultaneously. Two types of these implants are directly stimulating the remaining living cells in the retina. Hitherto the finest resolution has been achieved with the subretinal implants. Although the epiretinal implant offer lower resolution, but requires shorter surgery for implantation. Retinal implants in certain retinal diseases are proved to be capable of generating vision-like experiences. A number of types of retinal implants can be expected to appear in clinical practice a few years after the successful conclusion of clinical trials. Orv. Hetil., 2011, 152, 537–545

Изследване на динамичното поведение на Клетъчно Невронни Модели с приложения в разпознаване и обработка на образи

ИМИ-БАН, 09.11.2012 г., присъждане на образователна и научна степен "доктор" на Виктория Колева Рашкова по научна специалност 01.01.13. математическо моделиране и приложение на математиката. [Rashkova Victoria Koleva; Рашкова Виктория Колева

Aspects of algorithms and dynamics of cellular paradigms

Els paradigmes cel·lulars, com les xarxes neuronals cel·lulars (CNN, en anglès) i els autòmats cel·lulars (CA, en anglès), són una eina excel·lent de càlcul, al ser equivalents a una màquina universal de Turing. La introducció de la màquina universal CNN (CNN-UM, en anglès) ha permès desenvolupar hardware, el nucli computacional del qual funciona segons la filosofia cel·lular; aquest hardware ha trobat aplicació en diversos camps al llarg de la darrera dècada. Malgrat això, encara hi ha moltes preguntes a obertes sobre com definir els algoritmes d'una CNN-UM i com estudiar la dinàmica dels autòmats cel·lulars. En aquesta tesis es tracten els dos problemes: primer, es demostra que es possible acotar l'espai dels algoritmes per a la CNN-UM i explorar-lo gràcies a les tècniques genètiques; i segon, s'expliquen els fonaments de l'estudi dels CA per mitjà de la dinàmica no lineal (segons la definició de Chua) i s'il·lustra com aquesta tècnica ha permès trobar resultats innovadors.Los paradigmas celulares, como las redes neuronales celulares (CNN, eninglés) y los autómatas celulares (CA, en inglés), son una excelenteherramienta de cálculo, al ser equivalentes a una maquina universal deTuring. La introducción de la maquina universal CNN (CNN-UM, eninglés) ha permitido desarrollar hardware cuyo núcleo computacionalfunciona según la filosofía celular; dicho hardware ha encontradoaplicación en varios campos a lo largo de la ultima década. Sinembargo, hay aun muchas preguntas abiertas sobre como definir losalgoritmos de una CNN-UM y como estudiar la dinámica de los autómatascelular. En esta tesis se tratan ambos problemas: primero se demuestraque es posible acotar el espacio de los algoritmos para la CNN-UM yexplorarlo gracias a técnicas genéticas; segundo, se explican losfundamentos del estudio de los CA por medio de la dinámica no lineal(según la definición de Chua) y se ilustra como esta técnica hapermitido encontrar resultados novedosos.Cellular paradigms, like Cellular Neural Networks (CNNs) and Cellular Automata (CA) are an excellent tool to perform computation, since they are equivalent to a Universal Turing machine. The introduction of the Cellular Neural Network - Universal Machine (CNN-UM) allowed us to develop hardware whose computational core works according to the principles of cellular paradigms; such a hardware has found application in a number of fields throughout the last decade. Nevertheless, there are still many open questions about how to define algorithms for a CNN-UM, and how to study the dynamics of Cellular Automata. In this dissertation both problems are tackled: first, we prove that it is possible to bound the space of all algorithms of CNN-UM and explore it through genetic techniques; second, we explain the fundamentals of the nonlinear perspective of CA (according to Chua's definition), and we illustrate how this technique has allowed us to find novel results