55 results about "Spectral structure" patented technology

Information is encoded in an image signal by exploiting spectral differences between colors that appear the same when rendered. These spectral differences are detected using image sensing that discerns the spectral differences. Spectral difference detection methods include using sensor-synchronized spectrally-structured-light imaging, 3D sensors, imaging spectrophotometers, and higher resolution Bayer pattern capture relative to resolution of patches used to convey a spectral difference signal.

Orthogonal frequency division multiplexing (OFDM) receiver embodiments of the invention provide timing misalignment estimation by calculating the intra-baud timing differential. The preferred method exploits the spectral structure of the short-preamble in that a time delay in the time-domain is manifest as a phase rotation in the frequency-domain. The timing misalignment is determined by special processing the spectral peaks of the modified short-preamble. An alternative embodiment linearly combines the two long-preamble symbols to construct a single “best estimate” long-preamble symbol. A normalized dot product of the “best estimate” long-preamble symbol and the ideal on-baud symbol is computed to obtain the magnitude of the timing misalignment. A dot product between the “best estimate” long-preamble symbol and the time derivative of the ideal on-baud sampled sequence is computed to obtain the sign of the timing misalignment.

Generating electrode stimulation signals for an implanted electrode array is described. An acoustic audio signal is processed to generate band pass signals which represent associated bands of audio frequencies. Macro bands are defined, each of which characterizes multiple band pass signals. The macro bands are processed in a sequence of sampling intervals. For each sampling interval, the processing includes: i. extracting timing and energy information from each band pass signal to form requested stimulation events, ii. decimating the requested stimulation events to select a maximum energy band pass signal within each macro band, and iii. decimating each selected band pass signal based on a pulse selection inhibition function and preserving temporal and spectral structures of the band pass signals so as to generate stimulation event signals. The stimulation event signals are weighted with a weighting matrix reflecting patient-specific pitch perception characteristics to produce output electrode stimulation signals to the implanted electrode array.

A method for correcting an X-ray diffraction (XRD) profile measured by an X-ray diffraction imaging (XDi) system is provided. The XDi system includes an anode, a detector, and a control system. The method includes obtaining an emission spectrum of the anode using the control system. The emission spectrum includes spectral structures. The method further includes calculating a piecewise spectral-correction function using the spectral structures in the emission spectrum, obtaining a measured spectrum of an object, and applying the spectral-correction function to the measured spectrum to generate a spectrally-corrected measured spectrum.

The invention discloses a blind deconvolution infrared spectrogram super-resolution restoration method. The method comprises the steps of performing normalization processing on infrared spectral data; calculating a first-order derivative of spectral intensity after normalization; estimating the noise intensity of a spectrum according to the first-order derivative of the spectrum so as to determine the value of a regularization parameter; establishing an infrared spectrum model; and solving a high-resolution infrared spectrum by utilizing a Huber-Markov field, a spectral deconvolution algorithm and an alternating minimum optimal iteration algorithm. According to the method, noise suppression is enhanced in a flat region of the spectrum, and spectral structure preservation is enhanced in a steep region of the spectrum; for the used Fourier infrared spectrum, the spatial-domain iterative blind deconvolution algorithm is good in effect; when a signal-to-noise ratio is higher than 30 dB, the spectral resolution is increased by about 30%; and priori knowledge of Huber-Markov adaptive constraints is effectively utilized, the application of the infrared spectrum to the fields of target detection and identification as well as agriculture, biology, medical science, meteorology, space technology and petrochemical industry is promoted, and technical support is provided.

The invention relates to an audio Doppler characteristic quantification-based gesture identification method and belongs to the field of man-machine interaction. By utilizing a general audio playing and receiving device, a Doppler effect of an audio signal is extracted to realize gesture identification. The method comprises the steps of firstly playing the audio signal with a certain frequency by a loudspeaker; capturing the audio signal reflected by a human body through a microphone; forming an eigenvector set by extracting a fine spectral structure after Doppler frequency shift; and realizing gesture identification classification through gesture primitive segmentation and an HMM. The gesture identification precision is extremely high and the gesture types are rich; the difficulty of incapability of accurately identifying gestures with same absolute distance paths in a previous audio Doppler gesture identification technology is overcome; the calculation is simple; the practicality is high; and the method can be widely applied to the fields of somatosensory interaction, virtual reality, smart home and the like.

The invention relates to the technical field of infrared spectroscopy wavelength, and more specifically, relates to a novel infrared spectroscopy wavelength selection method based on sparse Bayesian study. The sparse optimized wavelength selection method utilizes the spectral structure priori knowledge and the related priori knowledge of co-linearity between spectrums. The provided method has the advantages of little calculation quantity, few adjustable parameters, and strong robustness. For the first time, the spectral structure priori knowledge and the related priori knowledge of co-linearity between spectrums are utilized, and the spectral partitioned sparse structure can be determined in a self-adapting mode. Then sparse Bayesian study algorithm is adopted to calculate out the optimal solution of the sparse optimization problem so as to screen out the best wavelength point combination. The provided method can be widely applied to the field of solid-phase / liquid-phase / gas-phase infrared spectrum wavelength selection.

The invention relates to a dual-rate DML device, a module and a calibration method, which belongs to the technical field of optical communication. The invention particularly relates to the dual-rate DML device with a built-in signal calibration circuit, the module and the calibration method. According to the invention, the signal calibration circuit is added into the device; PD pre-configuration is realized through a novel spectral structure; the control structure of a sequence-sharing multi-channel serial signal is used to feed back a monitoring signal to an electric drive to adjust drive current; the problem of crosstalk between backlight monitoring is reduced; and high-quality signal output under 25Gbps and 28Gbps dual modulation frequency is realized.

A signal processing system is described for a cochlear implant. A pre-processor filter bank processes an acoustic audio signal to generate band pass signals which represent associated bands of audio frequencies. An information extraction module defines macro bands, each of which characterizes multiple band pass signals, and processes the macro bands in a sequence of sampling intervals. For each sampling interval the information extraction module processing includes: i. extracting timing and energy information from each band pass signal to form requested stimulation events, ii. decimating the requested stimulation events to select a maximum energy band pass signal within each macro band, and iii. decimating each selected band pass signal based on a pulse selection inhibition function and preserving temporal and spectral structures of the band pass signals so as to generate stimulation event signals. A pulse weighting module weights the stimulation event signals with a weighting matrix reflecting patient-specific pitch perception characteristics to produce output electrode stimulation signals to the implanted electrode array.