That was an EXCELLENT post, if you think about it, time can only be measured from the past to the present, and by the time the present is recorded it's already the past. Any attempt to measure the future is impossible as the future can only speculated and hypothesized, you can't measure something that isn't even there yet. None of these OTC CEO's will ever give us anything concrete it's always vague, for example why couldn't the actual number of units sold be given in the Press Release.
On a second note, I've tried to explain to you that the NEUROSYNC device uses software to compare rf interference with your EEG waves. The device must then compare and differentiate between random noise and your brain waves.
EXAMPLE 1) SYNCHRONOUS SEQUENCE
A This is similar to how your brains works. This is because your brains eeg is a measurement of a cascade of individual neurons firing in a sequence. Whereas the total sum tally of neural discharges is either increasing or decreasing or maintaining the same overall rate of activity. An analogy of this, would be if you took a sidewalk and marked each square in succession 1 to 10. A person is then instructed that he or she can start on any square. Their objective is to either stay on that square or move forward or backward one square at a time as fast as they can without jumping over any squares.
SYNCHRONOUS SEQUENCE CONTROL DATA [5,6,7,8,9,9,8,7,6,5,4,3]
EXAMPLE 2) ASYNCHRONOUS SEQUENCE or RANDOM STATIC or typical rf interference
A good analogy of this would be when you turn on a radio and it is between channels and you hear is random static.
ASYNCHRONOUS SEQUENCE [5,7,2,2,9,6,5,2,1,9,8,3]
EXAMPLE 3)(SYNCHRONOUS SEQUENCE + ASYNCHRONOUS SEQUENCE)/ASYNCHRONOUS SEQUENCE = SYNCHRONOUS SEQUENCE
An analogy of this would be when you are tuning a radio to filter out the static or rf interference.
[5,6,7,8,9,9,8,7,6,5,4,3] + [5,7,2,2,9,6,5,2,1,9,8,3] =
[(5,5)(6,7)(7,2)(8,2)(9,9)(9,6)(8,5)(7,2)(6,1)(5,9)(4,8)(3,3)
STEP 1) if (#=#) then (#+#)/2 for all (#,#)
[(5)(6,7)(7,2)(8,2)(9)(9,6))(8,5)(7,2)(6,1)(5,9)(4,8)(3)
STEP 2)going from left to right eliminate all numbers out of synchronous sequence
[(5)(6)(7)(8)(9)(9)(8)(7)(6)(5)(4)(3)]
EXAMPLE 4)(SYNCHRONOUS SEQUENCE + ASYNCHRONOUS SEQUENCE + SYNCHRONOUS ANOMALIES)/ ASYNCHRONOUS SEQUENCES + SYNCHRONOUS ANOMALIES = SYNCHRONOUS SEQUENCE
An analogy of this would be when you are panning across the various radio channels to find a radio station that's broadcasting an emergency news bulletin. Your reception of the channel broadcasting the news is faint compared to the background static and another station playing a Rolling Stones song. Your mind will attempt to filter out the static and the Rolling Stones song and gather the important instructions from the broadcast. This is what the NEUROSYNC device must do, it must use algorithms to extract the fainter channel, the (synchronous sequence), and filter out the random static (asynchronous sequences) and the Rolling Stone song (synchronous anomalies).
[5,6,7,8,9,9,8,7,6,5,4,3]+[5,6,2,2,9,6,5,2,1,9,8,3]+[1,2,3,7,8,9,6,7,8,9,1,1] =
(5,5,1)(6,7,2)(7,2,3)(8,2,7)(9,9,8)(9,6,9)(8,5,6)(7,2,7)(6,1,8)(5,9,9)(4,8,1)(3,3,2)
STEP 1) condense sets by removing one of each duplicate
(5,1)(6,7,2)(7,2,3)(8,2,7)(9,8)(9,6)(8,5,6)(7,2)(6,1,8)(5,9)(4,8,1)(3,1)
STEP 2)factor out synchronous sequences
[5,6,7,8,9,9,8,7,6,5,4,3] [5,6,7,7,8,9,8,7,6,5,4,3] [5,6,7,8,8,9,8,7,6,5,4,3]
[1,2,2,2] [1,2,3,2] [6,6,7,6,5,4,3]
STEP 3)Cancel all incomplete sets and recombine complete sets and take the average value for each set rounded to the whole number and compare to the control, record all triple redundent sets to single digits.
(5)(6)(7)(8,7,8)(9,8,8)(9)(8)(7)(6)(5)(4)(3)
ALGORITHM SOLUTION [5,6,7,8,8,9,8,7,6,5,4,3]
CONTROL DATA [5,6,7,8,9.9,8,7,6,5,4,3]
Compare the actual starting Synchronous Sequence with the basic algorithm that I just created using just a string of 12 data points, you'll see that it is amazingly accurate. The NeuroSync software probably analyzes over 12 data points. When you attached a wire to your device and connected it to a bicycle, it did what it was programmed to do. It extracted a synchronous sequences from the asynchronous sequences and synchronous anomalies or (combined background interference) and generated the most probable match to an actual eeg signal.
AI
