Fusion of heterogeneous data sources: A quaternionic approach

Sequential fusion of three- and four- dimensional heterogeneous data is achieved in the quaternion space H. This way, data from multiple sensors are combined in order to achieve ldquoimproved accuraciesrdquo and more specific inferences that could not be performed by the use of only a single sensor. To this end, the quaternion LMS (QLMS) is proposed for the online fusion of hypercomplex data within the ldquodata fusion via vector spacesrdquo framework. Case studies on real-world signals such as environmental and financial time series are provided to support the proposed approach.