Abstract: A method and system of cognitive communication for generating non-interfering transmission, includes conducting radio scene analysis to find grey spaces using external signal parameters for incoming signal analysis without having to decode incoming signals. The disclosed cognitive communications system combines the areas of communications, signal processing, pattern classification and machine learning to detect the signals in the given spectrum of interests, extracts their features, classifies the signals in types, learns the salient characteristics and patterns of the signal and predicts their future behaviors. In the process of signal analysis, a classifier is employed for classifying the signals. The designing of such a classifier is initially performed based on selection of features of a signal detected and by selecting a model of the classifier.

Abstract: In a method of cognitive communication a system for generating non-interfering transmission, includes conducting radio scene analysis to find grey space using external signal parameters for incoming signal analysis without having to decode incoming signals.

Abstract: In a method of cognitive communication for non-interfering transmission, wherein the improvement comprises the step of conducting radio scene analysis to find not just the spectrum holes or White spaces; but also to use the signal classification, machine learning and prediction information to learn more things about the existing signals and its underlying protocols, to find the Gray space, hence utilizing the signal space, consisting of space, time, frequency (spectrum), code and location more efficiently.

Abstract: The system in one embodiment relates to tightly integrating parameter estimation, symbol hypothesis testing, decoding, and rate identification. The present invention provides Turbo-decoding for joint signal demodulation based on an iterative decoding solution that exploits error correction codes. The system iteratively couples an initial amplitude estimator, a symbol estimator, a bank of decoders, and a joint amplitude estimator to produce the symbol estimates.

Abstract: The system in one embodiment relates to tightly integrating parameter estimation, symbol hypothesis testing, decoding, and rate identification. The present invention provides Turbo-decoding for joint signal demodulation based on an iterative decoding solution that exploits error correction codes. The system iteratively couples an initial amplitude estimator, a symbol estimator, a bank of decoders, and a joint amplitude estimator to produce the symbol estimates.

Abstract: The system in one embodiment relates to tightly integrating parameter estimation, symbol hypothesis testing, decoding, and rate identification. The present invention provides Turbo-decoding for joint signal demodulation based on an iterative decoding solution that exploits error correction codes. The system iteratively couples an initial amplitude estimator, a symbol estimator, a bank of decoders, and a joint amplitude estimator to produce the symbol estimates.

Abstract: The system in one embodiment relates to tightly integrating parameter estimation, symbol hypothesis testing, decoding, and rate identification. The present invention provides Turbo-decoding for joint signal demodulation based on an iterative decoding solution that exploits error correction codes. The system iteratively couples an initial amplitude estimator, a symbol estimator, a bank of decoders, and a joint amplitude estimator to produce the symbol estimates.

Abstract: The system in one embodiment relates to tightly integrating parameter estimation, symbol hypothesis testing, decoding, and rate identification. The present invention provides Turbo-decoding for joint signal demodulation based on an iterative decoding solution that exploits error correction codes. The system iteratively couples an initial amplitude estimator, a symbol estimator, a bank of decoders, and a joint amplitude estimator to produce the symbol estimates.

Abstract: The system in one embodiment relates to tightly integrating parameter estimation, symbol hypothesis testing, decoding, and rate identification. The present invention provides Turbo-decoding for joint signal demodulation based on an iterative decoding solution that exploits error correction codes. The system iteratively couples an initial amplitude estimator, a symbol estimator, a bank of decoders, and a joint amplitude estimator to produce the symbol estimates.

Abstract: The system in one embodiment relates to tightly integrating parameter estimation, symbol hypothesis testing, decoding, and rate identification. The present invention provides Turbo-decoding for joint signal demodulation based on an iterative decoding solution that exploits error correction codes. The system iteratively couples an initial amplitude estimator, a symbol estimator, a bank of decoders, and a joint amplitude estimator to produce the symbol estimates.

Abstract: In a method of cognitive communication for non-interfering transmission, wherein the improvement comprises the step of conducting radio scene analysis to find not just the spectrum holes or White spaces; but also to use the signal classification, machine learning and prediction information to learn more things about the existing signals and its underlying protocols, to find the Gray space, hence utilizing the signal space, consisting of space, time, frequency (spectrum), code and location more efficiently. In a method of cognitive jamming where smart and energy efficient jamming techniques are suggested based on sensing, classification and machine learning of the existing signals.

Abstract: The present invention provides an efficient means of estimating symbols transmitted in a multi-user environment in overloaded or super-saturated conditions by employing a deferred decorrelating decision feedback detector. In one embodiment, the present invention comprises a parameter estimation unit, filter bank, overloaded whitener and decision tree-based hypothesis testing. Parameter estimation defines the matched filter bank, whitening filters, and the terms of the hypothesis testing module. The whitening filter partially decouples co-channel interference and partially whitens the noise. The decision tree approach defers decisions until more evidence is accumulated and is a generalization that encompasses the jointly optimal maximum likelihood detector as well as the simpler decision feedback detectors.

Abstract: A digital receiver automatically detects and non-coherently demodulates a multiplicity of interfering digitally modulated signals transmitted simultaneously at approximately the same carrier frequency. The receiver includes one or more antenna inputs (e.g., polarization and/or space diverse), a parameter estimator module, and a multiuser detector for estimating the data transmitted by each interfering signals and adapted to operate with at least one of a MUD algorithm with partially quantized prior information and a MUD algorithm based on prewhitened data.

Abstract: A Turbo multi-user detector (MUD) processing system in multiple access communications channels that decreases the likelihood of improper decoding of the final values of interest, thereby allowing for a reduction in the number of iterations performed and lowers complexity without negatively impacting performance. The present invention comprises a multi-user detector serially concatenated to two decoder sections in such a manner that data flows iteratively from the MUD and to each detector stage and back to the MUD to correct for errors.

Abstract: The present invention provides an efficient means of estimating symbols transmitted in a multi-user environment in overloaded or super-saturated conditions by employing a deferred decorrelating decision feedback detector. In one embodiment, the present invention comprises a parameter estimation unit, filter bank, overloaded whitener and decision tree-based hypothesis testing. Parameter estimation defines the matched filter bank, whitening filters, and the terms of the hypothesis testing module. The whitening filter partially decouples co-channel interference and partially whitens the noise. The decision tree approach defers decisions until more evidence is accumulated and is a generalization that encompasses the jointly optimal maximum likelihood detector as well as the simpler decision feedback detectors.

Abstract: A digital receiver automatically detects and non-coherently demodulates a multiplicity of interfering digitally modulated signals transmitted simultaneously at approximately the same carrier frequency. The receiver includes one or more antenna inputs (e.g., polarization and/or space diverse), a parameter estimator module, and a multiuser detector for estimating the data transmitted by each interfering signals and adapted to operate with at least one of a MUD algorithm with partially quantized prior information and a MUD algorithm based on prewhitened data.

Abstract: The present invention discloses a method for film archival based upon digitization of dye densities of the film. In particular, by using the analytical densities of the dyes and the dye concentrations at each pixel, the present invention provides a method for determining the color of the particular pixel where such color value is not influenced by aging of the film substrate or chemical degradation of the color dyes used. If the analytical densities of a film are known, then the concentration of each dye can be estimated by measuring the logarithm of the transmission of the film in as few as three frequency bands. The error involved in this digitization is a function of filter bandwidth and a function of the number of spectral transmission measurements used for the dye concentration estimation. The present invention is directly applicable in the field of film restoration and corresponding methods and devices for film restoration are disclosed.