k-Wave Toolbox

• Getting Started
• Run the First Example
• Build Your Own Simulation
• Troubleshooting
• Reference List
• Examples
• Initial Value Problems
• Example: Homogenous Propagation Medium
• Example: Using A Binary Sensor Mask
• Example: Defining A Sensor Mask By Opposing Corners
• Example: Loading External Image Maps
• Example: Heterogeneous Propagation Medium
• Example: Saving Movie Files
• Example: Recording The Particle Velocity
• Example: Defining A Gaussian Sensor Frequency Response
• Example: Comparison Of Modelling Functions
• Example: Setting An Initial Pressure Gradient
• Example: Simulations In One Dimension
• Example: Simulations In Three Dimensions
• Example: Photoacoustic Waveforms in 1D, 2D and 3D
• Time Varying Source Problems
• Example: Monopole Point Source In A Homogeneous Propagation Medium
• Example: Dipole Point Source In A Homogeneous Propagation Medium
• Example: Simulating Transducer Field Patterns
• Example: Steering A Linear Array
• Example: Snell's Law And Critical Angle Reflection
• Example: The Doppler Effect
• Example: Diffraction Through A Slit
• Example: Simulations In Three-Dimensions
• Sensor Directivity
• Example: Focussed Detector in 2D
• Example: Focussed Detector in 3D
• Example: Modelling Sensor Directivity in 2D
• Example: Modelling Sensor Directivity in 3D
• Example: Sensor Element Directivity in 2D
• Example: Focussed 2D Array with Directional Elements
• Photoacoustic Image Reconstruction
• Example: 2D FFT Reconstruction For A Line Sensor
• Example: 3D FFT Reconstruction For A Planar Sensor
• Example: 2D Time Reversal For A Line Sensor
• Example: 2D Time Reversal For A Circular Sensor
• Example: 3D Time Reversal For A Planar Sensor
• Example: 3D Time Reversal For A Spherical Sensor
• Example: Image Reconstruction With Directional Sensors
• Example: Image Reconstruction With Bandlimited Sensors
• Example: Iterative Image Improvement Using Time Reversal
• Example: Attenuation Compensation Using Time Reversal
• Example: Attenuation Compensation Using Time Variant Filtering
• Example: Automatic Sound Speed Selection
• Diagnostic Ultrasound Simulation
• Example: Defining An Ultrasound Transducer
• Example: Simulating Ultrasound Beam Patterns
• Example: Using An Ultrasound Transducer As A Sensor
• Example: Simulating B-mode Ultrasound Images
• Example: Simulating B-mode Images Using A Phased Array
• Numerical Analysis
• Example: Controlling The Absorbing Boundary Layer
• Example: Source Smoothing
• Example: Filtering A Delta Function Input Signal
• Example: Modelling Power Law Absorption
• Example: Modelling Nonlinear Wave Propagation
• Example: Optimising k-Wave Performance
• Using The C++ Code
• Example: Running C++ Simulations
• Example: Saving Input Files in Parts
• Elastic Wave Propagation
• Example: Explosive Source In A Layered Medium
• Example: Plane Wave Absorption
• Example: Shear Waves And Critical Angle Reflection
• Example: Simulations In Three Dimensions
• Functions - By Category
• Functions - Alphabetical List
• Release Notes
• License

k-Wave Toolbox

filterTimeSeries

Filter signal using the Kaiser windowing method

Syntax

filtered_signal = filterTimeSeries(kgrid, medium, signal)
filtered_signal = filterTimeSeries(kgrid, medium, signal, ...)

Description

filterTimeSeries filters an input time domain signal using a low pass filter applied by applyFilter with a specified cut-off frequency, stop-band attenuation, and transition bandwidth. It uses the Kaiser Windowing method to design the FIR filter, which can be implemented as either a zero phase or linear phase filter. The cutoff frequency is defined by a minimum number of temporal points per wavelength. A smoothing ramp can also be applied to the beginning of the signal to reduce high frequency transients.

Inputs

kgrid	k-Wave grid structure returned by makeGrid
medium	k-Wave medium structure
signal	the time domain signal to filter

Optional Inputs

Optional 'string', value pairs that may be used to modify the default computational settings.

Input	Valid Settings	Default	Description
'PlotSignals'	(boolean scalar)	false	Boolean controlling whether the time signal is displayed before and after filtering.
'PlotSpectrums'	(boolean scalar)	false	Boolean controlling whether the amplitude spectrum is displayed before and after filtering.
'PPW'	(integer numeric scalar)	3	The number of points per wavelength used to compute the filter cutoff frequency (setting to 0 turns of the filtering).
'RampPPW'	(integer numeric scalar)	0	The number of points per wavelength used to compute the length of the cosine start-up ramp (setting to 0 turns off the start-up ramp).
'StopBandAtten'	(numeric scalar)	60	Attenuation in decibels in the filter stop band.
'TransitionWidth'	(numeric scalar)	0.1	Size of the transition relative to the temporal sampling frequency.
'ZeroPhase'	(boolean scalar)	false	Boolean controlling whether a causal or zero phase filter is applied.

Outputs

filtered_signal

the filtered time signal

Examples

• Monopole Point Source In A Homogeneous Propagation Medium
• Dipole Point Source In A Homogeneous Propagation Medium
• Simulating Transducer Field Patterns
• The Doppler Effect
• Diffraction Through A Slit
• Simulations In Three-Dimensions
• Focussed Detector in 3D
• Modelling Sensor Directivity in 2D
• Modelling Sensor Directivity in 3D
• Focussed 2D Array with Directional Elements
• Filtering A Delta Function Input Signal

See Also

applyFilter, smooth, spectrum

expandMatrix

findClosest

© 2009-2014 Bradley Treeby and Ben Cox.