Closed-loop Feedback Process and Harmonic Balance

Algorithms of Harmonic Balance need to articulate and encapsulate beyond Global Variables because of higher cohesion and efficiency in Biological Systems. The harmonic establishment is one of the most cost-effective strategies that protect and boost Biological Systems against Invisible Entities Aggression. Algorithms beyond Harmonic Balance can promote productivity in system performances and improve social behavior patterns. Add designated algorithms can prevent the demand generation of Invisible Entities and attenuate exponentially against structural complexities, which appear on the evolutionary path of either system operations or activities. 

One of the substantial algorithms of Harmonic Balance is the closed-loop feedback process. It reduces overhead costs and extreme austerity measures in Non-Biological and Biological Systems. A Closed-loop feedback process as an indispensable algorithm in Harmonic Balance can be implemented through Input Channels. It plays a fundamental role in restoring a harmonious balance. 

 

The feedback process can modify and ensure resilient Non-Biological Systems as follows.

 

1- Unlocking Error Codes through Systematic Control.

2- High Attention to Code Execution.

3- Dynamic interactions with whole layers.

4- Divergence with Convergence Diagnosis for Harmonic Performances.

5- Update algorithm parameters according to Global Structure to minimize Random Breakdowns and Unexpected Expenses. 

Observation: 

According to experimental observations with goldfishes for three years, parameters of harmonic balance have been generated in goldfishes by gaining attention to environmental factors and dynamic interactions. Goldfishes live longer and happier than those other goldfishes without parameters of harmonic balance. Gestural exchanges and eye contact in dynamic interactions imply closed-loop Feedback.

 

Observation: 

Missing to articulate a Feedback Process on automating parameters within Global Variables urges Non-Biological Systems to develop in the waterfall life cycle model.

The iterative life cycle model creates comprehensive solutions for bugs on the evolutionary path of system performances. Systems Owners have better economic awareness of system environments and more perspective on Harmonic Balance for Biological Systems. However, implementing the life cycle model requires extra time and asset allowance. It is cost-effective to implement the iterative life cycle model in Non-Biological Systems.