International Conference on Computer and Knowledge Engineering

Home / 12th International Conference on Computer and Knowledge Engineering

A Hybrid Echo State Network for Hypercomplex Pattern Recognition, Classification, and Big Data Analysis

Authors :

Mohammad Jamshidi¹ Fatemeh Daneshfar²

1- University of West Bohemia 2- University of Kurdistan

Keywords :

machine learning،classification،octonion algebra،echo state network

Abstract :

Processing big data with high-dimensional forms is one the most challenging parts of analyzing different signals and systems for various applications, including decisionmaking, pattern recognition, classification, etc. This procedure can be more problematic when interpreting and modeling complex phenomena. On the other hand, the processing speed in machine learning (ML) methods may not be acceptable, especially for real-time implementations. In other words, the more accurate a signal is, the more latency can occur. Recently, echo state networks (ESN) have shown appropriate precession in signal processing and classifying variables. However, utilization of a reservoir layer affects their speed, particularly for high-dimensional data. This paper presents a powerful ESN method for pattern recognition and classification of complex phenomena based on a new octonion ESN called octonion nonlinear ESN (ONESN). This method includes a modified version of the conventional ESN, in which all computations from the real space are mapped to the octonion space. Consequently, the size of the reservoir and its weights are reduced to 1/8 of its initial amount, increasing the speed of processing. Also, a bilinear filter to improve the performance of the conventional ESN is added to the output of the network.

Papers List

List of archived papers

XAI for Transparent Autonomous Vehicles: A New Approach to Understanding Decision-Making in Self-driving Cars

Maryam Sadat Hosseini Azad - Amir Abbas Hamidi Imani - Shahriar Baradaran Shokouhi

A Comprehensive Approach to SMS Spam Filtering Integrating Embedded and Statistical Features

Shaghayegh Hosseinpour - Mohammad Reza Keyvanpour

Evolutionary Approach to GAN Hyperparameter Tuning: Minimizing Discriminator and Generator Loss Functions

Sajad Haghzad Klidbary - Anahita Babaei - Ramin Ghorbani

Predicting the Recovery Rate of COVID-19 Using a Novel Hybrid Method

Fatemeh Ahouz - Ebrahim Sayahi

Load Frequency Control of Geothermal Power Plant Incorporated Two-Area Hydro-Thermal System with AC-DC Lines

Shanker J Gambhire - Malligunta Kiran Kumar - Hossein Shahinzadeh - Mohammad-hossein Fayaz-dastgerdi - B. Srikanth Goud - Ch.Naga sai Kalyan

Adaptive-A-GCRNN: Enhancing Real-time Multi-band Spectrum Prediction through Attention-based Spatial-Temporal Modeling

Seyed majid Hosseini - Seyedeh Mozhgan Rahmatinia - Seyed Amin Hosseini Seno - Hadi Sadoghi yazdi

IR-LPR: Large Scale of Iranian License Plate Recognition Dataset

Mahdi Rahmani - Melika Sabaghian - Seyyedeh Mahila Moghadami - Mohammad Mohsen Talaie - Mahdi Naghibi - Mohammad Ali Keyvanrad

GroupRec: Group Recommendation by Numerical Characteristics of Groups in Telegram

Davod Karimpour - Mohammad Ali Zare Chahooki - Ali Hashemi

A Comprehensive Dataset of Real-scene Images for Text Detection and Recognition in Persian

Iman Souzanchi - Ramin Rahimi - Mohammad Ali Majidi Anvari - Atefeh Baniasadi - Ashkan Sadeghi - Mohammad Reza Mohammadi

T-Rank: Graph Data Analytics for Urban Traffic Modeling

Alireza Safarpour - Iman Gholampour - Amirhossain Aghazadeh Fard - Seyed Mohammad Karbasi

Samin Hamayesh - Version 42.4.1