Patent ID: 11875252
Assignee: nan
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 10:
11. An autonomous device controller having a neural network device for applying a trained neural network, the neural network including a sequence of neural network layers, wherein input data of the neural network device is applied to sensor data of an autonomous device, the neural network being configured to classify objects in the sensor data, an autonomous device control being configured for decision making depending on the classification, the neural network device is configured for applying the trained neural network, the neural network device comprising:
a communication interface for receiving the input data;
a non-transitory neural network storage configured to store trained parameters for multiple layers of the sequence of neural network layers; and
a processor system configured to apply the sequence of neural network layers to the input data, wherein
at least one layer of the sequence of neural network layers, both during training and in the trained neural network, is a projection layer, the projection layer being configured for a summing parameter, the summing parameter being at least 2, and is configured to project a layer input vector of the projection layer to a projection layer output vector in a limited multi label (LML) polytope which is a set of points in a unit hypercube with coordinates that sum to the summing parameter, the projecting including optimizing a layer loss-function applied to the projection layer output vector subject to the condition that the projection layer output vector sums to the summing parameter, wherein the layer loss-function includes a regulating term and a projection term, wherein optimizing the layer loss function includes applying an iterated approximation algorithm to obtain the projection layer output vector.