Programmable retinal dynamics in a CMOS mixed-signal array processor chip

The low-level image processing that takes place in the retina is intended to compress the relevant visual information to a manageable size. The behavior of the external layers of the biological retina has been successfully modelled by a Cellular Neural Network, whose evolution can be described by a set of coupled nonlinear differential equations. A mixed-signal VLSI implementation of the focal-plane low-level image processing based upon this biological model constitutes a feasible and cost effective alternative to conventional digital processing in real-time applications. For these reasons, a programmable array processor prototype chip has been designed and fabricated in a standard 0.5μm CMOS technology. The integrated system consists of a network of two coupled layers, containing 32 × 32 elementary processors, running at different time constants. Involved image processing algorithms can be programmed on this chip by tuning the appropriate interconnections weights. Propagative, active wave phenomena and retina-like effects can be observed in this chip. Design challenges, trade-offs, the buildings blocks and some test results are presented in this paper.Office of Naval Research (USA) N00014-00-10429European Community IST-1999-19007Ministerio de Ciencia y Tecnología TIC1999-082

Review of CMOS implementations of the CNN universal machine-type visual microprocessors

While in most application areas digital processors can solve problems initially, in some fields their capabilities are very limited. A typical example is vision. Simple animals outperform super-computers in the realization of basic vision tasks. In order to overcome the limitations of these conventional systems, a fundamentally different array architecture is needed. This architecture is based on the new paradigm of analogic cellular (CNN) computing whose most advanced implementation is the so-called CNN universal machine (CNN-UM). Its main components are: a) parallel architecture consisting of an array of locally-connected analog processors; b) a means of storing, locally, pixel-by-pixel, the intermediate computation results, and c) stored on-chip programmability. When implemented as a mixed-signal VLSI chip, the CNN-UM is capable of image processing at rates of trillions of operations per second with very small size and low power consumption. On the other hand, when integrating the adaptive multi-sensor array in the CNN-UM, the resulting sensor+computer array offers unprecedented capabilities. This paper reviews the latest results on CMN-UM chips and systems, and outlines the envisaged roadmap for these computers.European Union IST-1999-19007Comisión Interministerial de Ciencia y Tecnología TIC99-082

CMOS realization of a 2-layer CNN universal machine chip

Some of the features of the biological retina can be modelled by a cellular neural network (CNN) composed of two dynamically coupled layers of locally connected elementary nonlinear processors. In order to explore the possibilities of these complex spatio-temporal dynamics in image processing, a prototype chip has been developed by implementing this CNN model with analog signal processing blocks. This chip has been designed in a 0.5/spl mu/m CMOS technology. Design challenges, trade-offs and the building blocks of such a high-complexity system (0.5 /spl times/ 10/sup 6/ transistors, most of them operating in analog mode) are presented in this paper.Office of Naval Research (USA) N-00014-00-1-0429Comisión Interministerial de Ciencia y Tecnología TIC-1999-082

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

Bio-inspired analog parallel array processor chip with programmable spatio-temporal dynamics

A bio-inspired model for an analog parallel array processor (APAP), based on studies on the vertebrate retina, permits the realization of complex spatio-temporal dynamics in VLSI. This model mimics the way in which images are processed in the natural visual pathway which renders a feasible alternative for the implementation of early vision tasks in standard technologies. A prototype chip has been designed and fabricated in 0.5 /spl mu/m CMOS. Design challenges, trade-offs and the building blocks of such a high-complexity system (0.5/spl times/10/sup 6/ transistors, most of them operating in analog mode) are presented in this paper.Comisión Interministerial de Ciencia y Tecnología TIC1999-082

A Bio-Inspired Two-Layer Mixed-Signal Flexible Programmable Chip for Early Vision

A bio-inspired model for an analog programmable array processor (APAP), based on studies on the vertebrate retina, has permitted the realization of complex programmable spatio-temporal dynamics in VLSI. This model mimics the way in which images are processed in the visual pathway, what renders a feasible alternative for the implementation of early vision tasks in standard technologies. A prototype chip has been designed and fabricated in 0.5 μm CMOS. It renders a computing power per silicon area and power consumption that is amongst the highest reported for a single chip. The details of the bio-inspired network model, the analog building block design challenges and trade-offs and some functional tests results are presented in this paper.Office of Naval Research (USA) N-000140210884European Commission IST-1999-19007Ministerio de Ciencia y Tecnología TIC1999-082

Second-order neural core for bioinspired focal-plane dynamic image processing in CMOS

Based on studies of the mammalian retina, a bioinspired model for mixed-signal array processing has been implemented on silicon. This model mimics the way in which images are processed at the front-end of natural visual pathways, by means of programmable complex spatio-temporal dynamic. When embedded into a focal-plane processing chip, such a model allows for online parallel filtering of the captured image; the outcome of such processing can be used to develop control feedback actions to adapt the response of photoreceptors to local image features. Beyond simple resistive grid filtering, it is possible to program other spatio-temporal processing operators into the model core, such as nonlinear and anisotropic diffusion, among others. This paper presents analog and mixed-signal very large-scale integration building blocks to implement this model, and illustrates their operation through experimental results taken from a prototype chip fabricated in a 0.5-μm CMOS technology.European Union IST 2001 38097Ministerio de Ciencia y Tecnología TIC 2003 09817 C02 01Office of Naval Research (USA) N00014021088

Method and System for Object Recognition Search

A method for object recognition using shape and color features of the object to be recognized. An adaptive architecture is used to recognize and adapt the shape and color features for moving objects to enable object recognition

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

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