Lists of Interesting Patents on interestingoldpatents.com
Check out the interesting patents such as US6470214, on interestingoldpatents.com. You can copy the full list and verify they are still active patents and not believed to be fraudulent on USPTO.gov official database. The following post is about creating audio files that are encoded in the form ready to be transmitted using SSB, for causing the Radio Hearing Effect.
The lists of patents provided have fascinated me for a long time. There are inventions such as how to make people feel bugs on their skin with magentic resonance. Or how to make people percieve voices in their head likt the code in this article describes.
When Thinking About Patents Like The Ones for The Radio Hearing Effect its Pertinant to Remember
Patents are not usually considered to be proof that a patent exists. But, they are proof that a rational patent assessor believed the idea was real and working. The patent assessor also confirmed that they believed instructions to build the invention were adequitely provided in the patent itself before publishing.
Patent US6470214
Patent US6470214 describes the precise mathematical methods for creating a Carrier Suppressed AM signal, and precisely how to encode the audio to create the Radio Hearing effect using circuitry. Now that we have wider access to modern mathematical libraries in programming, its actually much simpler than it appears. You can use the data included included in the patent to create the program below to encode audio file and transmit it on any frequency. You can then transmit the signal using basically just any old ham radio at short range.
Although I haven’t tested this myself. You can test it, I share the code below for encoding the audio. Simply adjust the carrier frequency in Hz and transmit using SSB modulation on any frequency at a power level that permeates the body, such as 15W on the 70cm ham radio band at 1 meter away. The Radio Hearing Effect (Microwave Hearing Effect) is much more effective when using higher frequencies like microwaves. Higer frequencies (not higher wavelengths) are absorbed much better by the body (and specifically the brain). Which is in turn due to the fact the wave effectively travels more distance in a shorter space.
“Consequently, a message can be recognized as speech when a listener is preadvised that speech has been sent. However, if the listener does not know the content of the message, the audio signal is unintelligible.”
Quote from US6470214
When you are reading the patent, remember the demodulator for the radio hearing effect is biological, it is the auditory coretex itself.
The Code: Encoding Audio For The Radio Hearing Effect According to US6470214
The code below is python code. It takes a wav file as input and adjusts it. It does this so that when it resonates in the auditory coretex it causes an intelligable sound. This is distinct from recieveing the audio in a regualar circuit. When compared to a regular circuit, the auditory coretex is 3D. Regular circuits are just a one dimensional signal in a wire.
The code preprocesses the audio signal by applying a compensation filter. This de-emphasizes the high frequency content by 40 dB per decade. Which compensates for the natural roll-off of the specific acoustic impedance of the brain. The nature of the encoding means it is different for a signal on a different frequency. The following code encodes the audio for transmission on any specific frequency. You can use it to create audio to transmit. If you transmit it at a high enough power to permiate the body it will cause the Radio Hearing Effect on any frequency.
import numpy as np
from scipy.signal import hilbert
from scipy.io import wavfile
#%%
sample_rate, audio_signal = wavfile.read('/Users/felix/Downloads/audiowav.wav')
if audio_signal.ndim == 2:
# Convert to mono by averaging the two channels
audio_signal = np.mean(audio_signal, axis=1)
#%%
carrier_frequency = 144430000
analytic_signal = hilbert(audio_signal)
t = np.arange(len(audio_signal)) / sample_rate
ssb_signal = np.real(analytic_signal * np.exp(2j * np.pi * carrier_frequency * t))
ssb_signal_normalized = ssb_signal / np.max(np.abs(ssb_signal))
ssb_signal_pcm = np.int16(ssb_signal_normalized * 32767)
wavfile.write('ssb_output.wav', sample_rate, ssb_signal_pcm)
print("SSB signal has been written to 'ssb_output.wav'")Other Topics on This Site That Can Answer Topics Widely Regarded as Conspiracies
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