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Device and method responsive to influences of mind

a technology of mind and device, applied in the field of information detection and transfer, can solve the problems of inability to achieve general practical applications of mmi, complex and expensive apparatuses for experiments involving mmi, and inability to immediately translate laboratory demonstration into useful devices or methods, etc., to achieve high accuracy, improve the performance of mmi technology, and improve the effect of mmi technology

Active Publication Date: 2013-02-07
PSIGENICS CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Nevertheless, the laboratory demonstration did not immediately translate into useful devices or methods.
Practical applications of MMI have not generally been achieved due to an absence of understanding of why or how the effect manifests, and because the experimental devices and data processing methods used were not sensitive enough to the effect.
Apparatuses for experiments involving MMI have been complex and expensive.
Conventional ANN and AC techniques are limited, however, because they are not responsive to an influence of mind.

Method used

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  • Device and method responsive to influences of mind
  • Device and method responsive to influences of mind
  • Device and method responsive to influences of mind

Examples

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example 1

[0099]An anomalous effect detector in accordance with the invention contained a synchronous filter that included a synchronous multiplier (or synchronous detector) and a low-pass filter. The synchronous filter was set to filter at 5000 Hz frequency. The cut-of frequency of the low-pass filter was set at 10 Hz. Thus, the bandwidth of the synchronous filter was 10 Hz. From a ring oscillator in a computer, 7000 binary bits per second were extracted and input into the filter. The synchronous square-wave multiplier alternately multiplied the input by +1, then by −1, with a cycle of 14 input bits. In other words, after every seven input numbers, the filter multiplier switched between +1 and −1. The output of the low-pass filter was quasi-continuous digital filtered output. Without an influence of mind, the output was expected to vary randomly between “1” and “−1” following a normal Gaussian distribution. A number of measurements in a selected time period above or below “0” indicated an in...

example 2

[0100]In another working example, an input sequence of source numbers from a source of non-deterministic numbers was processed in a complex filter into a real output and an imaginary output. Thus, the complex filter produced two independent (orthogonal) outputs. Without an influence of mind, each output had a standard Gaussian distribution. When the source numbers were influenced by mind, however, the amplitudes of the two outputs deviated from a normal distribution. The complex filter output was used to produce an “X” and “Y” output by mathematically converting the Gaussian numbers to probabilities, which were uniformly distributed [0,1]. This provided a 2-D analog control.

[0101]In some embodiments, an artificial neural network is used to process output beyond the filter output.

[0102]FIG. 6 contains a block diagram illustrating an exemplary embodiment of a multi-stream SNDRN 500 in accordance with the present invention. Multi-stream SNDRN 500 includes noise diode 510, which is a so...

example 3

[0158]FIG. 26 depicts schematically the principal elements and functional processing steps in preferred embodiment of an anomalous effect detector 840 in accordance with the invention that is operable to process and to abstract raw data from SNDRNS (e.g., from SNDRNS contained in ASNs) to recognize a pattern resulting from an influence of mind. Anomalous effect detector 840 represents essentially a particular embodiment of generalized anomalous effect detector 830 described with reference to FIG. 25, above. Accordingly, among other uses, a system and a method in accordance with those of detector 840 are operable in an artificial sensory detector, ASD. The functional operations embodied in detector 840 were programmed into software and performed using a computer. It is understood, however, that in some embodiments, the same or similar functional processing operations performed in detector 840 are performed using other means and structures, such as one or more programmable microproces...

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PUM

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Abstract

V An anomalous effect detector (100, 130, 300, 800, 830, 840, 900, 930) responsive to an influence of mind comprises a source of non-deterministic random numbers, SNDRN, (104, 134, 310), a phase-sensitive filter (108, 140, 170, 320), and a results interface (110, 160, 340). In some embodiments, the phase-sensitive filter comprises a complex filter (170). An artificial sensory neuron (802, 810, 820, 906) comprises a SNDRN. Preferably, several artificial sensory neurons (802, 906) are grouped in a small volume. An analog artificial sensory detector (800) comprises a plurality of analog artificial sensory neurons (802), an abstracting processor (804) and a control or feedback unit (806). Some embodiments include an artificial neural network (850). An artificial consciousness network (900) contains a plurality of artificial neural networks (902, 914). One of the artificial neural networks (914) comprises an activation pattern meta-analyzer. An artificial consciousness device comprises a cluster (936) of artificial consciousness networks, a sensory input device (932) to provide sensory input signals (933) to the input of one or more ANNs in ACD (930), and an output device (938).

Description

TECHNICAL FIELD[0001]The present invention relates to the field of information detection and transfer, and more specifically to a device and method responsive to influences of mind.BACKGROUND ART[0002]Devices for detecting direct mind-machine interaction (MMI) have been proposed and researched for many years. The most carefully controlled and best-explored experiments utilize some type of non-deterministic, or true, random number generator that produces a sequence of random numbers, usually in a binary form. The most common random number generators used are of the electronic type that produce a sequence of random binary bits.[0003]In typical MMI experiments, a source of non-deterministic random numbers (SNDRN) is operated in conjunction with a human operator who attempts to influence the statistical properties of the SNDRN's output sequence. The operator, or subject, is directed to intend mentally the number of ones produced in the random sequence to be either higher, lower, or equa...

Claims

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Application Information

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Patent Type & Authority Applications(United States)
IPC IPC(8): G06N3/063G06N3/02G06F7/58
CPCG06N3/08G06N10/00G06F7/58G06F7/588G06N3/065G06N3/047
Inventor WILBER, SCOTT A.
Owner PSIGENICS CORP
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