A finite impulse response (FIR) filter has a defined length for its impulse response.
Approximating the complex impulse response with a simplified model can reduce computational burden.
Careful consideration must be given to the excitation signal when measuring the impulse response.
Changes in the impulse response can indicate damage or degradation of the system.
Characterizing the loudspeaker's impulse response is essential for high-fidelity audio reproduction.
Deconvolving the signal with the measured impulse response removed the room's acoustic signature.
Knowing the impulse response allows us to predict the output for any given input signal.
Modifying the system parameters alters the characteristics of the impulse response.
The acoustic characteristics of the room were analyzed using its measured impulse response.
The algorithm accurately estimated the system's impulse response from noisy data.
The algorithm estimates the impulse response from input and output data.
The auditory system processes sound by effectively analyzing the impulse response of the ear canal.
The control system's design was optimized based on the predicted impulse response.
The data acquisition system captured the impulse response with high accuracy.
The deconvolution process aims to recover the original signal from the recorded impulse response.
The design of the filter was guided by the desired impulse response.
The differences in impulse response between different rooms were significant.
The early reflections in the impulse response contribute to the perceived spaciousness of the room.
The effect of feedback on the system's impulse response was analyzed.
The engineer used the impulse response to diagnose the source of the echo in the communication channel.
The goal is to design a system with a desirable impulse response characteristic.
The goal was to minimize the duration of the impulse response.
The ideal impulse response would be a perfect Dirac delta function.
The impulse response can be used to simulate the system's response to complex signals.
The impulse response can reveal the presence of nonlinearities in the system.
The impulse response provides insight into the system's internal workings.
The impulse response reveals how a system reacts to a sudden, brief input.
The impulse response serves as a fingerprint of the system's dynamic behavior.
The impulse response was analyzed to identify the dominant resonant frequencies.
The impulse response was found to be affected by the system's operating environment.
The impulse response was found to be different for different frequencies.
The impulse response was found to be different for different input levels.
The impulse response was found to be different for different locations within the system.
The impulse response was found to be different for different signal polarities.
The impulse response was found to be highly dependent on the input signal's amplitude.
The impulse response was found to be sensitive to changes in temperature.
The impulse response was found to be sensitive to changes in the load impedance.
The impulse response was found to be sensitive to changes in the surrounding environment.
The impulse response was found to be sensitive to changes in the system's parameters.
The impulse response was measured using a specialized microphone array.
The impulse response was used to create a realistic simulation of the audio system.
The impulse response was used to create a realistic simulation of the building's acoustics.
The impulse response was used to create a realistic simulation of the environment.
The impulse response was used to create a realistic simulation of the instrument's sound.
The impulse response was used to create a realistic simulation of the speaker's performance.
The impulse response was used to create a virtual acoustic environment.
The impulse response was used to create a virtual acoustic space.
The impulse response was used to create a virtual instrument.
The impulse response was used to create a virtual reality environment.
The impulse response was used to create a virtual sound environment.
The impulse response was used to design an equalizer to compensate for the system's deficiencies.
The impulse response was used to determine the system's damping ratio.
The impulse response was used to identify and correct for distortions in the audio signal.
The impulse response was used to validate the simulation model.
The later parts of the impulse response contain information about the reverberation.
The length of the impulse response directly impacts the computational complexity of convolution.
The measured impulse response revealed significant reflections within the enclosure.
The modeling of the impulse response considered both direct sound and reflections.
The presence of noise can significantly degrade the accuracy of the estimated impulse response.
The quality of the recording was assessed by examining the sharpness of the impulse response.
The researcher investigated the relationship between the system's structure and its impulse response.
The room's impulse response was captured using a swept-sine measurement technique.
The shape and duration of the impulse response are key factors in determining the system's stability.
The shape of the impulse response provides clues about the system's physical properties.
The software allows users to visualize and manipulate the impulse response.
The study explores methods for efficiently computing the impulse response of complex systems.
The study focused on characterizing the impulse response of the cochlea.
The system's impulse response was analyzed to determine its frequency response.
The system's impulse response was analyzed to determine its group delay.
The system's impulse response was analyzed to determine its rise time.
The system's impulse response was analyzed to determine its settling time.
The system's impulse response was analyzed to determine its stability margin.
The system's impulse response was analyzed to determine its stability.
The system's impulse response was analyzed to determine its transient response.
The system's impulse response was analyzed to optimize its performance.
The system's impulse response was compared to theoretical predictions.
The system's impulse response was found to be highly nonlinear.
The system's impulse response was measured in both the time and frequency domains.
The system's impulse response was measured under various operating conditions.
The system's impulse response was used to create a virtual reality experience.
The system's impulse response was used to identify and correct for amplitude distortions.
The system's impulse response was used to identify and correct for errors in the calibration.
The system's impulse response was used to identify and correct for harmonic distortions.
The system's impulse response was used to identify and correct for intermodulation distortions.
The system's impulse response was used to identify and correct for nonlinear distortions.
The system's impulse response was used to identify and correct for phase distortions.
The system's impulse response was used to identify and correct for time-invariant distortions.
The system's impulse response was used to identify and mitigate sources of interference.
The system's non-minimum phase behavior was evident in the shape of its impulse response.
The system's performance was evaluated based on its measured impulse response.
The system's stability can be determined by examining the decay of its impulse response.
The system's transfer function is simply the Fourier transform of its impulse response.
The system's transient behavior is completely described by its impulse response.
The system’s identification relied heavily on an accurate measurement of its impulse response.
The theoretical impulse response was used as a benchmark for the experimental results.
The truncated impulse response can lead to artifacts in the processed signal.
The use of an ideal impulse response is often impossible to realize in practice.
Understanding the impulse response is crucial for designing effective digital filters.
We approximated the system's behavior by modeling its impulse response as a simple exponential decay.
We need to carefully analyze the impulse response to mitigate unwanted noise.