摘要:
An apparatus for decoding data segments representing a time-domain data stream, a data segment being encoded in the time domain or in the frequency domain, a data segment being encoded in the frequency domain having successive blocks of data representing successive and overlapping blocks of time-domain data samples. The apparatus includes a time-domain decoder for decoding a data segment being encoded in the time domain and a processor for processing the data segment being encoded in the frequency domain and output data of the time-domain decoder to obtain overlapping time-domain data blocks. The apparatus further includes an overlap/add-combiner for combining the overlapping time-domain data blocks to obtain a decoded data segment of the time-domain data stream.
摘要:
An audio encoder has a common preprocessing stage, an information sink based encoding branch such as spectral domain encoding branch, a information source based encoding branch such as an LPC-domain encoding branch and a switch for switching between these branches at inputs into these branches or outputs of these branches controlled by a decision stage. An audio decoder has a spectral domain decoding branch, an LPC-domain decoding branch, one or more switches for switching between the branches and a common post-processing stage for post-processing a time-domain audio signal for obtaining a post-processed audio signal.
摘要:
An audio encoder has a common preprocessing stage, an information sink based encoding branch such as spectral domain encoding branch, a information source based encoding branch such as an LPC-domain encoding branch and a switch for switching between these branches at inputs into these branches or outputs of these branches controlled by a decision stage. An audio decoder has a spectral domain decoding branch, an LPC-domain decoding branch, one or more switches for switching between the branches and a common post-processing stage for post-processing a time-domain audio signal for obtaining a post-processed audio signal.
摘要:
For classifying different segments of a signal which has segments of at least a first type and second type, e.g. audio and speech segments, the signal is short-term classified on the basis of the at least one short-term feature extracted from the signal and a short-term classification result is delivered. The signal is also long-term classified on the basis of the at least one short-term feature and at least one long-term feature extracted from the signal and a long-term classification result is delivered. The short-term classification result and the long-term classification result are combined to provide an output signal indicating whether a segment of the signal is of the first type or of the second type.
摘要:
This invention discloses a system to automate a non-destructive test (NDT) for measuring stress or stress change developed within an object during a certain time period by using unmanned aerial vehicles (UAV) and ultrasound technique. The system comprises a ground control station (GCS), UAVs and reference positioning modules as its basis. Given a test plan containing test points over a surface of a test object in 3D point coordinates, UAVs can fly autonomously to the points and perform ultrasound measurements on them with a single or a plurality of ultrasound transducers in an automated manner. Moreover, after receiving trigger signals from the GCS, a UAV can also perform the flight and the measurement synchronously with other UAVs. After a measurement, an acquired ultrasound echo signal is taken with another echo signal acquired at a different time point to compute stress or stress change.
摘要:
For classifying different segments of a signal which has segments of at least a first type and second type, e.g. audio and speech segments, the signal is short-term classified on the basis of the at least one short-term feature extracted from the signal and a short-term classification result is delivered. The signal is also long-term classified on the basis of the at least one short-term feature and at least one long-term feature extracted from the signal and a long-term classification result is delivered. The short-term classification result and the long-term classification result are combined to provide an output signal indicating whether a segment of the signal is of the first type or of the second type.