This brief explores the optimization of distributed-ROM-based finite state machine (FSM) implementations as an alternative to conventional implementations based on look-up tables (LUTs). In distributed-ROM implementations, LUTs with constant output value (called constant LUTs) and LUTs with the same content (called equivalent LUTs) can be saved. We propose a methodology to implement FSMs using distributed ROM that includes: 1) a greedy state encoding algorithm; 2) an algorithm to find the way of interconnecting the address signals to the ROM that maximize the number of constant or equivalent LUTs; and 3) a set of architectures to implement the columns of the ROM. The results obtained have been compared with conventional LUT-based implementations using standard benchmarks. The proposed technique reduces the number of LUTs in a 91% of cases and increases the speed in all cases.

A binary-tree-based finite state machine (BT-FSM) is a state machine with a 1-bit input signal whose state transition graph is a binary tree. BT-FSMs are useful in those application areas where searching in a binary tree is required, such as computer networks, compression, automatic control, or cryptography. This paper presents a new architecture for implementing BT-FSMs which is based on the model finite virtual state machine (FVSM). The proposed architecture has been compared with the general FVSM and conventional approaches by using both synthetic test benches and very large BT-FSMs obtained from a real application. In synthetic test benches, the average speed improvement of the proposed architecture respect to the best results of the other approaches achieves 41% (there are some cases in which the speed is more than double). In the case of the real application, the average speed improvement achieves 155%.

Finite state machines with input multiplexing (FSMIMs) have been proposed in previous works as a technique for efficient mapping FSMs into ROM memory. In this paper, we propose a new architecture for implementing FSMIMs, called FSMIM with state-based input selection, whose goal is to achieve a further reduction in memory usage. This paper also describes in detail the algorithms for generating FSMIMs used by the tool FSMIM-Gen, which has been developed and made available on the Internet for free public use. A comparative study in terms of speed and area between FSMIM approaches and other field programmable gate array-based techniques is presented. The results show that the FSMIM approaches obtain huge reductions in the look-up table (LUT) usage by using a small number of embedded memory blocks. In addition, speed improvements over conventional LUT-based implementations have been obtained in many cases.

Address-event-representation (AER) is a communication protocol that emulates the nervous system's neurons communication, and that is typically used for transferring images between chips. It was originally developed for bio-inspired and real-time 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. In this paper several software methods for generating AER streams from images stored in a computer's memory are presented. A hardware version that works in real-time is also being studied. All of them have been evaluated and compared.

Tuning a fuzzy system to meet a given set of input/output patterns is usually a difficult task that involves many parameters. This paper presents an study of different approaches that can be applied to perform this tuning process automatically, and describes a CAD tool, named xfsl, which allows applying a wide set of these approaches: (a) a large number of supervised learning algorithms; (b) different processes to simplify the learned system; (c) tuning only specific parameters of the system; (d) the ability to tune hierarchical fuzzy systems, systems with continuous output (like fuzzy controller) as well as with categorical output (like fuzzy classifiers), and even systems that employ user-defined fuzzy functions; and, finally, (e) the ability to employ this tuning within the design flow of a fuzzy system, because xfsl is integrated into the fuzzy system development environment Xfuzzy 3.0.

Describes a HW/SW codesign methodology for the implementation of fuzzy controllers on a platform composed of a general-purpose microcontroller and specific processing elements implemented on FPGAs or ASICs. The different phases of the methodology, as well as the CAD tools used in each design stage, are presented, with emphasis on the fuzzy system development environment Xfuzzy. Also included is a practical application of the described methodology for the development of a fuzzy controller for a dosage system.