INESC-ID

About: INESC-ID is a nonprofit organization based out in Lisbon, Portugal. It is known for research contribution in the topics: Field-programmable gate array & Control theory. The organization has 932 authors who have published 2618 publications receiving 37658 citations.

FantasyA - the duel of emotions

Abstract: FantasyA is a computer game where two characters face each other in a duel and emotions are used as the driving elements in the action decision of the characters. In playing the game, the user influences the emotional state of his or her semi-autonomous avatar using a tangible interface for affective input, the SenToy. In this paper we show how we approached the problem of modelling the emotional states of the synthetic characters, and how to combine them with the perception of the emotions of the opponents in the game. This is done by simulating the opponents action tendencies in order to predict their possible actions. For the user to play, he or she must understand the emotional state of his opponent which is achieved through animations (featuring affective body expressions) of the character. FantasyA was evaluated with 30 subjects from different ages and the preliminary results showed that the users liked the game and were able to influence the emotional states of their characters, in particular the young users.

QBF-based boolean function Bi-decomposition

Abstract: Boolean function bi-decomposition is ubiquitous in logic synthesis. It entails the decomposition of a Boolean function using two-input simple logic gates. Existing solutions for bi-decomposition are often based on BDDs and, more recently, on Boolean Satisfiability. In addition, the partition of the input set of variables is either assumed, or heuristic solutions are considered for finding good partitions. In contrast to earlier work, this paper proposes the use of Quantified Boolean Formulas (QBF) for computing bi-decompositions. These bi-decompositions are optimal in terms of the achieved quality of the input set of variables. Experimental results, obtained on representative benchmarks, demonstrate clear improvements in the quality of computed decompositions, but also the practical feasibility of QBF-based bi-decomposition.

D-ADMM based distributed MPC with input-output models

Abstract: This article presents a distributed model pre- dictive controller (MPC) based on linear models that use input/output plant data and D-ADMM optimization. The use of input/output models has the advantage of not requiring a Kalman filter to estimate the plant state. The D-ADMM algorithm solves the optimization problem associated to a cost function that is the sum of the control agents private costs, being a modification of the Alternating Direction of Multipliers (ADMM) algorithm that requires no central node and implies a significant reduction in the communication among adjacent nodes. The distributed MPC is obtained for the special case of a linear graph. An application to distributed control of a water delivery canal is presented to illustrate the algorithm.

Design of High-Speed Viterbi Decoders on Virtex-6 FPGAs

Abstract: The Viterbi algorithm is one of the most popular algorithms for decoding convolutional codes. Implementing a high-speed Viterbi decoder is a challenging task due to the recursive iteration of an add-compare-select operation. In this paper, we propose and analyze several optimization techniques to improve the area/performance tradeoffs of high speed Viterbi decoders on Virtex-6 FPGAs. Both Radix-2, Radix-4 and a modified radix-4 add-compare-select units are implemented with these techniques. The implementation reports for a Virtex-6 FPGA indicate that the proposed techniques achieve very efficient designs of Viterbi decoders in terms of performance and area. 360 Mbps are achievable with radix-2 solutions, while radix-4 solutions can achieve 430 Mbps, better than previous state-of-the-art solutions. Higher data rates can only be achieved with other parallelization techniques, like the sliding block method