Embedding Multi-Task Address-Event- Representation Computation

Address-Event-Representation, AER, is a communication protocol that is intended to transfer neuronal spikes between bioinspired chips. There are several AER tools to help to develop and test AER based systems, which may consist of a hierarchical structure with several chips that transmit spikes among them in real-time, while performing some processing. Although these tools reach very high bandwidth at the AER communication level, they require the use of a personal computer to allow the higher level processing of the event information. We propose the use of an embedded platform based on a multi-task operating system to allow both, the AER communication and processing without the requirement of either a laptop or a computer. In this paper, we present and study the performance of an embedded multi-task AER tool, connecting and programming it for processing Address-Event information from a spiking generator.Ministerio de Ciencia e Innovación TEC2006-11730-C03-0

Test Infrastructure for Address-Event-Representation Communications

Address-Event-Representation (AER) is a communication protocol for transferring spikes between bio-inspired chips. Such systems may consist of a hierarchical structure with several chips that transmit spikes among them in real time, while performing some processing. To develop and test AER based systems it is convenient to have a set of instruments that would allow to: generate AER streams, monitor the output produced by neural chips and modify the spike stream produced by an emitting chip to adapt it to the requirements of the receiving elements. In this paper we present a set of tools that implement these functions developed in the CAVIAR EU project.Unión Europea IST-2001-34124 (CAVIAR)Ministerio de Ciencia y Tecnología TIC-2003-08164-C03-0

Synthetic Generation of Events for Address-Event-Representation Communications

Address-Event-Representation (AER) is a communications protocol for transferring images between chips, originally developed for bio-inspired image processing systems. Such systems may consist of a complicated hierarchical structure with many chips that transmit images among them in real time, while performing some processing (for example, convolutions). In developing AER based systems it is very convenient to have available some kind of means of generating AER streams from on-computer stored images. In this paper we present a method for generating AER streams in real time from images stored in a computer’s memory. The method exploits the concept of linear feedback shift register random number generators. This method has been tested by software and compared to other possible algorithms for generating AER streams. It has been found that the proposed method yields a minimum error with respect to the ideal situation. A hardware platform that exploits this technique is currently under development

Spike-based control monitoring and analysis with Address Event Representation

Neuromorphic engineering tries to mimic biological information processing. Address-Event Representation (AER) is a neuromorphic communication protocol for spiking neurons between different chips. We present a new way to drive robotic platforms using spiking neurons. We have simulated spiking control models for DC motors, and developed a mobile robot (Eddie) controlled only by spikes. We apply AER to the robot control, monitoring and measuring the spike activity inside the robot. The mobile robot is controlled by the AER-Robot tool, and the AER information is sent to a PC using the USBAERmini2 interface.Junta de Andalucía P06-TIC-01417Ministerio de Educación y Ciencia TEC2006-11730-C03-0

Arbitrated address event representation digital image sensor

80×60 (1/8 VGA) address event imager in 0.6 μm CMOS converts light intensity into a one-bit code (a spike). The read-out of each spike is initiated by the pixel. The dynamic range is 200 dB for a pixel and 120 dB for the array. It uses 3.4 mW at a spike rate of 200 kHz. It is capable of 8.3 k effective frames/s

An Approach to Distance Estimation with Stereo Vision Using Address-Event-Representation

Image processing in digital computer systems usually considers the visual information as a sequence of frames. These frames are from cameras that capture reality for a short period of time. They are renewed and transmitted at a rate of 25-30 fps (typical real-time scenario). Digital video processing has to process each frame in order to obtain a result or detect a feature. In stereo vision, existing algorithms used for distance estimation use frames from two digital cameras and process them pixel by pixel to obtain similarities and differences from both frames; after that, depending on the scene and the features extracted, an estimate of the distance of the different objects of the scene is calculated. Spike-based processing is a relatively new approach that implements the processing by manipulating spikes one by one at the time they are transmitted, like a human brain. The mammal nervous system is able to solve much more complex problems, such as visual recognition by manipulating neuron spikes. The spike-based philosophy for visual information processing based on the neuro-inspired Address-Event-Representation (AER) is achieving nowadays very high performances. In this work we propose a two- DVS-retina system, composed of other elements in a chain, which allow us to obtain a distance estimation of the moving objects in a close environment. We will analyze each element of this chain and propose a Multi Hold&Fire algorithm that obtains the differences between both retinas.Ministerio de Ciencia e Innovación TEC2009-10639-C04-0

From Vision Sensor to Actuators, Spike Based Robot Control through Address-Event-Representation

One field of the neuroscience is the neuroinformatic whose aim is to develop auto-reconfigurable systems that mimic the human body and brain. In this paper we present a neuro-inspired spike based mobile robot. From commercial cheap vision sensors converted into spike information, through spike filtering for object recognition, to spike based motor control models. A two wheel mobile robot powered by DC motors can be autonomously controlled to follow a line drown in the floor. This spike system has been developed around the well-known Address-Event-Representation mechanism to communicate the different neuro-inspired layers of the system. RTC lab has developed all the components presented in this work, from the vision sensor, to the robot platform and the FPGA based platforms for AER processing.Ministerio de Ciencia e Innovación TEC2006-11730-C03-02Junta de Andalucía P06-TIC-0141

Tools for Address-Event-Representation Communication Systems and Debugging

Address-Event-Representation (AER) is a communications protocol for transferring spikes between bio-inspired chips. Such systems may consist of a hierarchical structure with several chips that transmit spikes among them in real time, while performing some processing. To develop and test AER based systems it is convenient to have a set of instruments that would allow to: generate AER streams, monitor the output produced by neural chips and modify the spike stream produced by an emitting chip to adapt it to the requirements of the receiving elements. In this paper we present a set of tools that implement these functions developed in the CAVIAR EU project.European Commission IST-2001-34124Ministerio de Ciencia y Tecnología TIC-2003-08164-C03-0

Software Generation of Address-Event-Representation for Interchip Images Communications

Address-Event-Representation (AER) is a communications protocol for transferring images between chips, originally developed for bio-inspired image processing systems. Such systems may consist of a complicated hierarchical structure with many chips that transmit images among them in real time, while performing some processing (for example, convolutions). In developing AER based systems it is very convenient to have available some kind of means of generating AER streams from on-computer stored images. In this paper we present a method for generating AER streams in real time from images stored in a computer’s memory. The method exploits the concept of linear feedback shift register random number generators. This method has been tested by software and compared to other possible algorithms for generating AER streams. It has been found that the proposed method yields a minimum error with respect to the ideal situation. A hardware platform that exploits this technique is currently under development