Abstract: Systems and methods for visualizations of music may include one or more processors which receive an audio input, and compute a simulation of a human auditory periphery using the audio input. The processor(s) may generate one or more visual patterns on a visual display, according to the simulation, the one or visual patterns synchronized to the audio input.

Abstract: Systems and methods for counter-phased binocular stimulation may include a device that determines a target frequency of a stimulation response. The device may output a first visual stimulation at a first frequency and a first phase to a first eye. The device may output a second visual stimulation at a second frequency and a second phase to a second eye. The first visual stimulation and the second visual stimulation may together produce the stimulation response at the target frequency.

Abstract: Systems and methods for counter-phased binocular stimulation may include a device that determines a target frequency of a stimulation response. The device may output a first visual stimulation at a first frequency and a first phase to a first eye. The device may output a second visual stimulation at a second frequency and a second phase to a second eye. The first visual stimulation and the second visual stimulation may together produce the stimulation response at the target frequency.

Abstract: Systems and methods for visualizations of music may include one or more processors which receive an audio input, and compute a simulation of a human auditory periphery using the audio input. The processor(s) may generate one or more visual patterns on a visual display, according to the simulation, the one or visual patterns synchronized to the audio input.

Abstract: A controller for real-time visual display of music includes a music analysis module and a display control module. The music analysis module receives an audio input, determines human perceived musical structures, human felt affect and emotion as a function of the audio input, and outputs a signal corresponding to the determined structure, affect and emotion. The display control module is operatively coupled to the music analysis module and receives the signal and controls a visual display as a function thereof to express the determined musical structure, affect and emotion in a visual manner.

Abstract: A controller for real-time visual display of music includes a music analysis module and a display control module. The music analysis module receives an audio input, determines human perceived musical structures, human felt affect and emotion as a function of the audio input, and outputs a signal corresponding to the determined structure, affect and emotion. The display control module is operatively coupled to the music analysis module and receives the signal and controls a visual display as a function thereof to express the determined musical structure, affect and emotion in a visual manner.

Abstract: A method for learning connections between nonlinear oscillators in a neural network comprising the steps of providing a plurality of nonlinear oscillators, with each respective oscillator producing an oscillation distinct from the others in response to an input and detecting an input at an at least first oscillator of the plurality of nonlinear oscillators. Detecting an input at an at least a second oscillator of the plurality of nonlinear oscillators, comparing the oscillation of the at least first oscillator to the oscillation of the at least second oscillator at a point in time, and determining whether there is coherency between the oscillation of the at least first oscillator and the oscillation of the at least second oscillator. Changing at least one of the amplitude and phase of a connection between the at least first oscillator and the at least second least oscillator as a function coherency between the at least first oscillator and the oscillation of the at least second oscillator.

Abstract: A method for mimicking the auditory system's response to rhythm of an input signal having a time varying structure comprising the steps of receiving a time varying input signal x(t) to a network of n nonlinear oscillators, each oscillator having a different natural frequency of oscillation and obeying a dynamical equation of the form r . = r ? ( ? + ? 1 ? ? z ? 2 + ? ? ? 2 ? ? z ? 4 1 - ? ? ? z ? 2 ) + c ? ? x ? ( t ) ? cos ? ? ? - r ? ? ? ? ? r 2 - 2 ? ? ? r ? ? cos ? ? ? + 1 ? . = ? + ? 1 ? r 2 + ? ? ? 2 ? r 4 1 - ? ? ? r 2 - c ? ? x ? ( t ) ? sin ? ( ? ) ? ? ? r 2 - 2 ? ? ? r ? ? cos ? ( ? ) + 1 ? ? ? . = - k ? ? x ? ( t ) ? sin ? ? ? ? ? ? r 2 - 2 ? ? ? r ? ? cos ? ? ? + 1 wherein ? represents the response frequency, r is the amplitude of the oscillator and ? is the phase of the oscillator.

Abstract: A method for mimicking the auditory system's response to rhythm of an input signal having a time varying structure comprising the steps of receiving a time varying input signal x(t) to a network of n nonlinear oscillators, each oscillator having a different natural frequency of oscillation and obeying a dynamical equation of the form r . = r ? ( ? + ? 1 ? ? z ? 2 + ? ? ? 2 ? ? z ? 4 1 - ? ? ? z ? 2 ) + c ? ? x ? ( t ) ? cos ? ? ? - r ? ? ? ? ? r 2 - 2 ? ? ? r ? ? cos ? ? ? + 1 ? . = ? + ? 1 ? r 2 + ? ? ? 2 ? r 4 1 - ? ? ? r 2 - c ? ? x ? ( t ) ? sin ? ( ? ) ? ? ? r 2 - 2 ? ? ? r ? ? cos ? ( ? ) + 1 ? ? ? . = - k ? ? x ? ( t ) ? sin ? ? ? ? ? ? r 2 - 2 ? ? ? r ? ? cos ? ? ? + 1 wherein ? represents the response frequency, r is the amplitude of the oscillator and ? is the phase of the oscillator.

Abstract: A method for learning connections between nonlinear oscillators in a neural network comprising the steps of providing a plurality of nonlinear oscillators, with each respective oscillator producing an oscillation distinct from the others in response to an input and detecting an input at an at least first oscillator of the plurality of nonlinear oscillators. Detecting an input at an at least a second oscillator of the plurality of nonlinear oscillators, comparing the oscillation of the at least first oscillator to the oscillation of the at least second oscillator at a point in time, and determining whether there is coherency between the oscillation of the at least first oscillator and the oscillation of the at least second oscillator. Changing at least one of the amplitude and phase of a connection between the at least first oscillator and the at least second least oscillator as a function coherency between the at least first oscillator and the oscillation of the at least second oscillator.

Abstract: The present invention is directed to systems and methods designed to ascertain the structure of acoustic signals. The approach involves an alternative transform of an acoustic input signal, utilizing a network of nonlinear oscillators in which each oscillator is tuned to a distinct frequency. Each oscillator receives input and interacts with the other oscillators in the network, yielding nonlinear resonances that are used to identify structure in an acoustic input signal. The output of the nonlinear frequency transform can be used as input to a system that will provide further analysis of the signal. According to one embodiment, the nonlinear responses are defined as a network of n expanded canonical oscillators zi, with an input, for each oscillator as a function of an external stimulus. In this way, the response of oscillators to inputs that are not close to its natural frequency are accounted for.

Abstract: The present invention relates to systems and methods for processing acoustic signals, such as music and speech. The method involves nonlinear frequency analysis of an incoming acoustic signal. In one aspect, a network of nonlinear oscillators, each with a distinct frequency, is applied to process the signal. The frequency, amplitude, and phase of each signal component are identified. In addition, nonlinearities in the network recover components that are not present or not fully resolvable in the input signal. In another aspect, a modification of the nonlinear oscillator network is used to track changing frequency components of an input signal.

Abstract: A method and apparatus for the analysis of a non-stationary signal to determine the presence of pseudo-periodic components in the signal. The present invention possesses a memory for recent events, displays expectations for upcoming events, and can handle missing events at those times. The apparatus ignores events which should not effect its prediction. These properties are achieved by driving one or more nonlinear oscillators with an input signal, causing a subset of the oscillators to entrain to pseudo-periodic components of the input signal. When incoming events fall within one of the pulses produced by a nonlinear oscillator, the nonlinear oscillator adjusts it phase and/or period to synchronize with the input signal.