CliffoSor, an innovative FPGA-based architecture for geometric algebra

A brief introduction to Clifford algebra

Geometric algebra (also known as Clifford algebra) is a powerful mathematical tool that offers a natural and direct way to model geometric objects and their transformations. It is gaining growing attention in different research fields as physics, robotics, CAD/CAM and computer graphics. Clifford algebra makes geometric objects (points, lines and planes) into basic elements of computation and defines few universal operators that are applicable to all types of geometric elements. This paper provides an introduction to Clifford algebra elements and operators.

Biometric Features for Mobile Agents Ownership

Multi-Agent System (MAS) architectures can be used for e-Business application due their flexibility, scalability and interoperability. Agent ownership implies that a specific person or organization (the owner) is responsible for the agent's actions. Agents, whose ownership was certainly fixed, could operate on behalf of their owner to make transactions, to buy or sell products. Security requirements in the agent ownership setting process are the identification of the owner and the protection of the identification information carried by an agent. In this paper, we investigate the possibility of using biometrics in mobile agent systems for owner authentication. Biometric features can be used …

Web Directories as a Knowledge Base to Build a Multi-Agent System for Information Sharing

. A neural based multi-agent system, exploiting the Web Directories as a Knowledge Base for information sharing and documents retrieval, is presented. The system is based on the E?Net architecture, a neural network capable of learning the activation function of its hidden units and having good generalization capabilities. System goal is to retrieve, among documents shared by a networked community, documents satisfying a query and dealing with a specific topic. The system is composed by four agents: the Trainer Agent, the Neural Classifier Agent, the Interface Agent, and the Librarian Agent. The sub-symbolic knowledge of the Neural Classifier Agent is automatically updated each time a new, n…

A fast fusion technique for fingerprint and iris spatial descriptors in multimodal biometric systems

Multimodal biometric identification systems aim to combine two or more physical or behavioral traits to provide optimal False Acceptance Rate (FAR) and False Rejection Rate (FRR). In this paper a new fusion technique for fingerprint and iris spatial descriptors with a low execution time is presented. The report focuses on spatial fusion strategies, offering and proposing a modern perspective on multi-biometrics. In greater detail, a spatial-based approach and a homogeneous biometric vector, integrating iris and fingerprint data, are generated, fused, and processed for the overall system matching score. The goal of this approach is to demonstrate that, by using spatial iris features followin…

A Neural Multi-Agent Architecture for an Autonomous Mobile Robot Control

The aim of this paper is to introduce a multi-agent architecture for an autonomous robot control oriented to obtain high design modularity and high parallelism of decision processes. A multi-agent approach allows us to design several specialized agents and each of them is optimized in order to solve a single part of the whole task. Each agent is able to cooperate with other agent exchanging information, so the robot is able to make the appropriate policy of management to reach a prefixed goal. We tested the proposed architecture with a simple application: an autonomous mobile robot performs object retrieval tasks into unknown structured environments. The robot is not given a priori map of t…

Biometrics authentication and reputation based policies in a mas security framework

An embedded iris recognizer for portable and mobile devices

Software-intensive systems play an increasingly dominant role in our lives and daily activities. Several applications, in which a timely response to user and environment stimulus is essential, require real-time software intensive systems. Computation-intensive applications, such as video compression, control systems, security systems, result in significant growth for processor workload. To address the above issues, one possible solution is to design embedded specialized components. At the same time, the integration of new features in portable and mobile devices is rapidly increasing. Several services and applications require robust user authentication for access to services, data, and resou…

Fast Convergence of Neural Networks by Application of a New Min-Max Algorithm

Abstract The paper presents a new application of the min-max method, an original algorithm previously successfully applied in other areas and based on a combination of the quasi-Newton and steepest descent methods in order to find the weights minimising the error function of a feed forward neural networks. Preliminary results, obtained by applying the proposed method to a simple 2-2-1 architecture on small Boolean learning problems, are very promising.