Principles of White Noise

In an effort to continue with my most recent blogs, which have mostly been focused on light and sound, or more precisely sound and electromagnetic waves, I wanted to introduce you to the principles of white noise.  White noise is something often referred to by paranormal investigators and researchers but few actually understand the concept.  It is my hope with this article to bring some of the fundamentals of white noise to light and explain how these concepts could apply to investigations and research.

In this case, “white” is an adjective that we use to describe a type of noise because of the way light works.  I know you must be thinking, “Well, what does noise have to do with how light works?”  That is certainly a viable question.  White light is light that consists of all different frequencies (or colors) of light combined together.  More to the point, it is White Electromagnetic Radiation.  Most people know of the familiar prism with a rainbow separating light back into its component colors as it passes through.  White noise can be thought of this way.  It is a combination of all different frequencies of sound.  It is a sound or series of constant sounds that contain every frequency typically within the range of human hearing.  In the same way that the color white contains the whole spectrum of colors of light, similarly, white noise is created by using the entire spectrum of frequencies usually heard by the human ear.

Most people think white noise, which is also called white sound, is simply “noise” but this is not the case.  It is actually a signal, a sound frequency.

Most of us are aware that there are varying “colors” of noise.  The different “colors” of noise have significantly different properties.  Audio signals, for instance, will sound different to humans whereas images will have a visibly different texture.    This is why specific applications will require a noise of a different “color”.  The different colors of noise include, but are not limited to:

–  White;

–  Pink;

–  Brown;

–  Blue;

–  Violet;

–  Grey;

–  Red;

–  Green; and

–  Black.

The specific differences involve a lot of math and sound engineering knowledge.  It can be very complicating so I will not go into those details right now.

White noise is used to “mask” other sounds.  In technical terms, it is described as noise in which the amplitude is constant throughout the audible frequency range.  The common misconception about white noise is that it is only associated with “static”.  However, “white noise”  is used as a general description for any type of constant unchanging background sound.  Examples include, but are not limited to:

  • Sounds of nature, such as rain, waves crashing on a shoreline, or crickets chirping;
  • Sound of machinery, such as air conditioning units, a washing machine, or a fan; and
  • Ambient soundscapes, such as the roar of an aircraft engine or a crackling fire.

This is the reason many people use some form of white noise when attempting to sleep.

It may sound counterproductive to add more noise when you are trying to sleep.  However, it works because of the science behind white noise, which blends frequencies together resulting in a masking effect.  For instance, some people will use white noise to drown out annoying external sounds, such as a dog’s incessant barking outside or people talking.  It blends these sounds into the overall background noise.  When this happens, your brain pays less attention and can begin to relax.  When you add the noise, you are implementing what is called Sound Masking, which instead of actually drowning out the sounds, they become masked by the frequencies of the white noise.

The information above is the reason why I do not usually utilize white noise generators when my focus is primarily on sound-related evidence.  Based on our experiments and research, doing so actually lessens your chances of capturing decent sound-related evidence – because the white noise tends to mask potential evidence.  Unfortunately, we can only speculate.  It is not yet clear whether or not this would apply to EVPs that are electromagnetic in nature rather than a result of a sound wave.  If the EVP is not a sound wave, this concept may or may not apply but we do not have anything absolutely conclusive at this point.  This is one aspect of EVP-research we have been exploring with our Gateway experiment, which is still ongoing.  Presumably, we suspect it would apply regardless because of the science of waves in general.  Any sound wave can be represented visually as an image depending on the equipment and software you are using to analyze.

The problem is this.  If the frequency of the potential EVP comes through at an amplitude that is lower than the white noise (the background noise), it will become drowned out by the energy of the frequency with the higher amplitude – the white noise itself.  In other words, the white noise will inadvertently mask the EVP.  We have all seen this phenomenon at one point or another.  We think we may hear something on a recording but it sounds too muffled and may be unintelligible.  Or, the reverse will happen.  You will hear the sound wave with your own ears but the equipment will appear to not have captured it.  We believe this is one reason why.  The background noise, the white noise of the area you are in, has higher amplitudes than the amplitude of the sound being recorded. assuming it is a sound wave, and becomes “masked”, meaning it is still there but you will not hear it on the recording itself upon play back.  Modern digital recorders were specifically designed to limit the amount of background noise recorded resulting in a higher quality of recording.  I believe this is one reason why you can capture better evidence on modern digital recorders than you can with older recorders.

Of course, this is just a basic hypothesis.  We believe there are other factors that play perhaps an even more significant role, such as wave interference.