Abstract: According to one embodiment, an anomaly detection apparatus includes a processing circuit configured to calculate a reconstruction error of an input signal being a time-series signal, calculate cycle information indicating cyclic property of the reconstruction error, and determine presence/absence of an anomaly signal in the input signal on the basis of the cycle information or the cycle information and the reconstruction error.

Abstract: According to one embodiment, an anomaly detection apparatus includes a processing circuit configured to calculate a reconstruction error of an input signal being a time-series signal, calculate cycle information indicating cyclic property of the reconstruction error, and determine presence/absence of an anomaly signal in the input signal on the basis of the cycle information or the cycle information and the reconstruction error.

Abstract: A signal processing apparatus includes one or more processors. The one or more processors perform first-type signal processing on an input signal using a neural network, and output a first-type output signal. The one or more processors convert the first-type output signal into a second-type output signal for calculating a first-type loss related to accuracy of second-type signal processing performed by another signal processing device The one or more processors calculate the first-type loss based on the second-type output signal and a correct signal. The one or more processors optimize parameters of the neural network based on the first-type loss.

Abstract: According to an embodiment, a processing apparatus includes a hardware processor. The hardware processor is configured to: cut out, from an input signal, a plurality of partial signals that are predetermined parts in the input signal; execute processing on the plurality of partial signals using neural networks having the same layer structure with each other to generate a plurality of intermediate signals including a plurality of signals corresponding to a plurality of channels; execute predetermined statistical processing on signals for each of the plurality of channels for each of the plurality of intermediate signals corresponding to the plurality of partial signals, to calculate statistics for each channel and generate a concatenated signal by concatenating the statistics of the plurality of respective intermediate signals for each channel; generate a synthetic signal by performing predetermined processing on the concatenated signal; and output an output signal in accordance with the synthetic signal.

Abstract: According to one embodiment, an information acquisition apparatus includes an emitter, a detector and processing circuitry. The emitter is configured to emit light. The detector is configured to detect the light reflected by a target. The processing circuitry is configured to acquire a plurality of distance indexes, the distance indexes being based on time differences between emission and detection of the light, and generate distance information regarding a distance to the target based on a frequency distribution of the acquired distance indexes or a statistic calculated from the frequency distribution.

Abstract: According to one embodiment, an inference apparatus includes a processor. The processor generates an intermediate signal by processing an input signal with a convolutional neural network. The processor extracts one or more intermediate partial signals each serving as part of the intermediate signal from the intermediate signal. The processor calculates a statistic of the one or more intermediate partial signals. The processor outputs an inference result relating to the input signal and corresponding to the statistic.

Abstract: According to an embodiment, a processing apparatus includes a hardware processor. The hardware processor is configured to: cut out, from an input signal, a plurality of partial signals that are predetermined parts in the input signal; execute processing on the plurality of partial signals using neural networks having the same layer structure with each other to generate a plurality of intermediate signals including a plurality of signals corresponding to a plurality of channels; execute predetermined statistical processing on signals for each of the plurality of channels for each of the plurality of intermediate signals corresponding to the plurality of partial signals, to calculate statistics for each channel and generate a concatenated signal by concatenating the statistics of the plurality of respective intermediate signals for each channel; generate a synthetic signal by performing predetermined processing on the concatenated signal; and output an output signal in accordance with the synthetic signal.

Abstract: This signal processing device includes one or more processors. The processors receive, as an input, an input signal that is a third signal obtained by superposing a second signal on a first signal or a fourth signal obtained by converting the third signal, and estimate a feature of the first signal on the basis of the input signal. The processors execute inference on the basis of the feature and outputs an inference result.

Abstract: An estimation device includes a controller and an estimator. The estimation device switches a plurality of control conditions which are set so that there is satisfied at least one of conditions that that irradiation patterns of irradiation light radiated to an object are different from each other under the plurality of control conditions, and that light receiving patterns to receive reflected light obtained by reflecting the irradiation light by the object are different from each other under the plurality of control conditions; and estimates characteristics of the object on the basis of object data related to the object acquired by receiving light from one or more light receiving gates under the plurality of control conditions.

Abstract: According to an embodiment, a first signal processing apparatus includes one or more hardware processors configured to function as a signal processing unit, a first signal adjustment unit, and an update unit. The signal processing unit is configured to perform first signal processing on an input signal in which a second signal is superimposed on a first signal using at least one parameter and to output a first restoration signal obtained by restoring the first signal. The first signal adjustment unit is configured to multiply at least one of the first signal and the first restoration signal by a weighting coefficient and to output a corrected first signal and a corrected first restoration signal. The update unit is configured to update the at least one parameter using an error between the corrected first signal and the corrected first restoration signal.

Abstract: A signal processing apparatus includes one or more processors. The one or more processors perform first-type signal processing on an input signal using a neural network, and output a first-type output signal. The one or more processors convert the first-type output signal into a second-type output signal for calculating a first-type loss related to accuracy of second-type signal processing performed by another signal processing device The one or more processors calculate the first-type loss based on the second-type output signal and a correct signal. The one or more processors optimize parameters of the neural network based on the first-type loss.