Abstract: Methods for signal processing employ instantaneous frequency analysis through quadrature genometric measurement of streaming signal data. Such methods may include the analysis of any composite analog periodic signal, including but not limited to audio, video, radio, seismic, light, radar, sonar, EKG, where signal data is streaming, stationary or non-stationary, and represents either linear or non-linear processes.

Abstract: Described is a technique for a backup and restoration of data in a network that includes a multi-lingual file system and a multi-lingual network file server. Multiple meta data files are associated with a single data file in the network. Provided are services for packaging the metadata as a single parameter of an application programming interface (API) for a particular data file being backed up or restored over a network. These techniques may be used in both full and incremental backups and restores of data over a network.

Abstract: Described is a technique for a backup and restoration of data in a network that includes a multi-lingual file system and a multi-lingual network file server. Multiple meta data files are associated with a single data file in the network. Provided are services for packaging the metadata as a single parameter of an application programming interface (API) for a particular data file being backed up or restored over a network. These techniques may be used in both full and incremental backups and restores of data over a network.

Abstract: A method and apparatus for signal classification using a multilayer temporal relaxation network involves receiving an input signal feature vector, classifying a first signal feature, and classifying a second signal feature using contextual information. The multilayer temporal relaxation network applies a relaxation process that updates an activation value of a node in a first layer and updates an activation value of a node in a second layer. The multilayer network then generates a signal classification according to an activation value of a node in the multilayer network.

Abstract: A system and method for identifying the phoneme sound types that are contained within an audio speech signal is disclosed. The system includes a microphone and associated conditioning circuitry, for receiving an audio speech signal and converting it to a representative electrical signal. The electrical signal is then sampled and converted to a digital audio signal with a digital-to-analog converter. The digital audio signal is input to a programmable digital sound processor, which digitally processes the sound so as to extract various time domain and frequency domain sound characteristics. These characteristics are input to a programmable host sound processor which compares the sound characteristics to standard sound data. Based on this comparison, the host sound processor identifies the specific phoneme sounds that are contained within the audio speech signal.

Abstract: A method of filtering images with a filter that is dependent on image type. For binary images, a fixed Laplacian filter is used for all pixels. For non-binary images, an automatic level-sensitive Laplacian filter is used. For non-binary images, Laplacian filter coefficients and normalization divisors are made a function of intensity on a pixel by pixel basis. Pixels indicating a high intensity may be greatly changed by neighboring pixels. Pixels indicating a low intensity receive relatively little or no filtering. In a specific example embodiment, the intensity range is divided to bands, with a different filter for each band. The resulting images are visually sharpened (edge enhanced) with very little impact in darker areas of the image.

Abstract: A system and method for identifying the phoneme sound types that are contained within an audio speech signal is disclosed. The system includes a microphone and associated conditioning circuitry, for receiving an audio speech signal and converting it to a representative electrical signal. The electrical signal is then sampled and converted to a digital audio signal with a digital-to-analog converter. The digital audio signal is input to a programmable digital sound processor, which digitally processes the sound so as to extract various time domain and frequency domain sound characteristics. These characteristics are input to a programmable host sound processor which compares the sound characteristics to standard sound data. Based on this comparison, the host sound processor identifies the specific phoneme sounds that are contained within the audio speech signal.