FIR (Finite Impulse Response) filters have a finite duration response to an impulse input, making them inherently stable and easy to design. They are typically used when linear phase is required, such as in audio processing. IIR (Infinite Impulse Response) filters have an infinite duration response, offering sharper cutoffs with fewer coefficients but can be unstable. They are preferred in applications where computational efficiency is critical, like real-time processing in embedded systems.

Optimizing DSP algorithms for embedded systems involves several strategies, including algorithm simplification, leveraging fixed-point arithmetic, and utilizing specialized DSP instructions. Profiling and benchmarking are crucial to identify bottlenecks. Memory access patterns are optimized to reduce latency, and parallel processing techniques are employed where applicable. Additionally, careful consideration of the hardware architecture, such as the use of DMA and cache optimization, is essential for achieving efficient performance.

In a previous project, I developed a real-time noise cancellation system for a headset. The challenge was achieving low latency while maintaining high noise reduction quality. I overcame this by implementing a hybrid approach combining adaptive filtering and spectral subtraction. Profiling helped identify and optimize critical sections, reducing latency by 30%. Additionally, I collaborated with the hardware team to optimize the audio pipeline, ensuring seamless integration and performance.

Ensuring accuracy and reliability involves rigorous testing and validation. Unit tests are created to verify individual components, while integration tests ensure the system works as a whole. Simulation and emulation are used to validate performance under various conditions. Statistical analysis and Monte Carlo simulations help account for variability. Continuous monitoring in production with automated alerts and regular audits ensure any deviations are promptly addressed, maintaining high reliability.

I have extensive experience with tools like MATLAB, Simulink, and Python for algorithm development and simulation. For embedded systems, I use tools such as TI's Code Composer Studio and ARM's Keil MDK. I am proficient in using debuggers, profilers, and oscilloscopes for hardware debugging. Additionally, I have experience with version control systems like Git and collaboration platforms like Jira for project management.