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AncientHeart369's avatar

What for you comprises a "friendly", local AI BCPS system vs the CCP AI BCPS, and how can the average person utilize it in a real-world way?

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Brandon, I've got a question regarding the Kalman Filter and how it works. I know about the extreme importance you place on cleaning up the electricity coming into the house. Better still, according to you, is to get off the grid entirely!

Anyway......are you saying that the Kalman Filter (algorithm) is somehow interfacing in our home wiring, all 60 hz devices, the electrical mains, etc, with the satellites, towers, etc to help facilitate Neurostrike and other bad actor AI BCI's? If so, like those lovely black boxes that exist in every town & city's power stations that transmit the mind control Lilly Wave, apparently the Kalman Filter can be mitigated/disrupted by the following (sourced from Brave AI):

"Firstly, a Kalman filter is an algorithm used to estimate the state of a system by combining predicted values with noisy measurements. In the context of home applications, it’s often employed in smart devices, such as fitness trackers or environmental sensors, to improve accuracy and reduce noise.

To disrupt a Kalman filter in the home, you’ll need to manipulate the inputs or outputs of the system, making it difficult for the algorithm to produce reliable estimates.

Methods to Disrupt a Kalman Filter in the Home:

Introduce deliberate noise: Use a device to generate artificial noise that mimics the sensor’s natural noise patterns. This can be done using a noise generator or by creating a simple circuit to introduce random fluctuations in the sensor’s output.

Modify sensor calibration: Adjust the sensor’s calibration settings to introduce systematic errors. This can be done by tweaking the sensor’s gain, offset, or sensitivity.

Introduce delayed or missing data: Simulate delayed or missing sensor readings by introducing artificial gaps in the data stream. This can be achieved using a simple timing circuit or software manipulation.

Use multiple, conflicting sensors: Install multiple sensors measuring the same parameter (e.g., temperature) and intentionally configure them to provide conflicting readings. This will challenge the Kalman filter’s ability to reconcile the differences and produce accurate estimates.

Apply external perturbations: Physically manipulate the environment or device to introduce external perturbations that affect the sensor’s readings. For example, you could use a fan to create air currents that disturb temperature sensors.

Important Notes:

Disrupting a Kalman filter in the home may not be desirable or necessary in most cases. Kalman filters are designed to improve accuracy and robustness in noisy environments. Be cautious when attempting to disrupt a Kalman filter, as it may have unintended consequences on the device’s performance or functionality."

ABOUT THE LILLY WAVE

Interesting Jeff Rense interview with Dr. Patrick Flanagan. Go to 07:30 for the meat of the conversation on how the Lilly Wave ultrasonic mind control is used in 60hz residential electric service.

https://www.youtube.com/watch?v=FzjzQDoGQgA

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