Optimizing MATLAB code is essential for improving performance, especially for complex computations. Here are some key strategies:

Preallocate Memory: Avoid dynamic resizing of arrays to enhance execution speed.
Vectorization: Replace loops with vectorized operations for efficiency.
Use Built-in Functions: MATLAB’s built-in functions are optimized for speed.
Optimize Loops: Minimize nested loops and use parfor for parallel computing.
Reduce Function Calls: Frequent function calls slow down execution; inline simple operations.
Profiling Tools: Use profile to identify bottlenecks.

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