Nokia Corporation

Nokia Siemens Networks Oy

Albert Höglund

Kimmo Hätönen

Antti Sorvari

Markus Juhani Miettinen

Jyrki Berg

Jaana Laiho

Kimmo Valkealahti

Sampo Kristian Torikka

Janne Pöllönen

Kari Kulmala

A method for teaching an anomaly detecting mechanism in a system comprising observable elements (), at least one of which has a periodic time-dependent behaviour, the anomaly detecting mechanism comprising a computerized learning mechanism (). The method comprises assembling indicators () indicating the behaviour of the elements () and arranging the assembled indicators such that each observable element's indicators are assigned to the same input data component. The learning mechanism () is taught so that the input data of the learning mechanism comprises the input data components which are based on the assembled indicators (). Points which approximate the input data are placed in the input space. A presentation of time (-) is incorporated into at least one input data component wherein the presentation of time is periodic, continuous and un-ambiguous within the period of the at least one element with periodic time-dependent behaviour.

Anomaly detection system and a method of teaching it

The present invention relates to a method and a cellular radio network device () for controlling the admission of user () to a cellular radio network (). In order to determine how much traffic is allowed in a cell (), threshold values are autotuned using quality measurements gathered during high load on a link. Thus, the network capacity is in increased while fulfilling desired quality requirements.

Method and device for controlling admission of users to a cellular radio network

A method and system for monitoring the behavior of at least one observable object, e.g. a network element, of a network, wherein at least one parameter of the observable object is repeatedly detected. An actually detected parameter is input to a learning process and to an analyzing process, wherein the learning process forms a reference, based on at least two detected parameter values, for describing the behavior of the observable object. The analyzing process compares the input parameter and the reference for detecting an anomal behavior. The parameter preferably is a vector which includes several values describing properties or functioning of the observable object, and is formed based on events and/or reports from the object.

System, device and method for automatic anomaly detection

Growing community of inventors

Helsinki, Finland

Albert Höglund