On a hybrid weightless neural system
نویسندگان
چکیده
A hybrid system using weightless neural networks (WNNs) and finite state automata is described in this paper. With the use of such a system, rules can be inserted and extracted into/from WNNs. The rule insertion and extraction problems are described with a detailed discussion of the advantages and disadvantages of the rule insertion and extraction algorithms proposed. The process of rule insertion and rule extraction in WNNs is often more natural than in other neural network models.
منابع مشابه
Generating and Classifying Recall Images by Neurosymbolic Computation
The neurosymbolic hybrid system ARCS, which extends a classifier for certain kinds of visually presented objects, generates recall images it is then capable of classifying. The modules performing classification are exploited for imagery, too. In particular, each weightless neural discriminator has been modified so as to generate a non-crisp example of the class of simple visual features it was ...
متن کاملParallel WiSARD object tracker: a ram-based tracking system
This paper proposes the Parallel WiSARD Object Tracker (PWOT), a new object tracker based on the WiSARD weightless neural network that is robust against quantization errors. Object tracking in video is an important and challenging task in many applications. Difficulties can arise due to weather conditions, target trajectory and appearance, occlusions, lighting conditions and noise. Tracking is ...
متن کاملTridimensional Pattern Reconstruction by Using Weightless Artificial Neural Networks
1. ABSTRACT This paper describes the structure and behavior of a system, composed by a set of weightless artificial neural networks, which is capable of learning different images and then reconstructing an image according to the closest learned pattern. This paper presents a technique which considers Hamming distance for pattern learning and reconstruction, therefore it is posible to study the ...
متن کاملDevelopment Mobile Robot Control Architecture with Integrated Planning and Control on Low Cost Microcontroller
This paper presents new hybrid control architecture-based interval type-2 nuro-fuzzy (IT2NF) for embedded mobile robot navigation where event-driven control is used to handle the dynamically changing of the environment. The proposed hybrid control architecture combining behavior-based reactive navigation and model-based environmental classification has been developed. Weightless neural network ...
متن کاملLearned Probabilistic Prediction in a Weightless Neural Network
This paper examines a weightless neural network traind to perform a probabilistic, iconic prediction task. The paper discusses both the network architecture and training scheme used. The iconic prediction task is examined both with and without a controlling input. Finally some speculative parallels are drawn between the system behaviour and prediction in biological systems.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- IJBIC
دوره 1 شماره
صفحات -
تاریخ انتشار 2009