An Adaptive Algorithm adjusts its parameters and strategy dynamically in response to changes in the environment or input data. This self-modification capability enables it to perform optimally under varying conditions, improving its efficiency and effectiveness over time.

• Digital Signal Processing: For noise reduction and signal enhancement.
• Machine Learning: In algorithms that adjust their learning rate or model complexity based on data.
• Network Security: In systems that dynamically adjust to detect and prevent new types of cyber threats.
• Financial Markets: For algorithmic trading strategies that adapt to changing market conditions.
• Telecommunications: For optimizing bandwidth and reducing interference.
• Healthcare: In adaptive diagnostic tools and treatment plans.

• Digital Signal Processing: An adaptive algorithm for noise cancellation adjusting filters to minimize noise.
• Machine Learning: A neural network modifying its learning rate based on performance metrics.
• Network Security: An intrusion detection system evolving its rules to catch new types of attacks.
• Financial Markets: An algorithmic trading bot altering its strategy in response to market volatility.

• Adaptive Algorithm – Wikipedia
• Adaptive Algorithms in Signal Processing
• Applications of Adaptive Algorithms in Network Security