Downsample

Resample input at lower rate by deleting samples

• Library:

• DSP System Toolbox / Signal Operations

Description

The Downsample block decreases the sampling rate of the input by deleting samples. When the block performs frame-based processing, it resamples the data in each column of the M_i-by-N input matrix independently. When the block performs sample-based processing, it treats each element of the input as a separate channel and resamples each channel of the input array across time. The resample rate is K times lower than the input sample rate, where K is the value of the Downsample factor parameter. The Downsample block resamples the input by discarding K–1 consecutive samples following each sample that is output.

This block supports triggered subsystems when you set the Rate options parameter to Enforce single-rate processing.

Ports

Input

Port_1 — Data input

column vector | matrix | N-D array

Data input whose sampling rate is to be decreased by the block, specified as a column vector or a matrix.

When you set the Input processing parameter to Elements as channels (sample based), the input can be an N-D array.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | Boolean | fixed point
Complex Number Support: Yes

Output

Port_1 — Downsampled output

column vector | matrix

Downsampled output with a sampling rate that is 1/K times the input sampling rate, returned as a column vector or a matrix.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | Boolean | fixed point
Complex Number Support: Yes

Parameters

Downsample factor, K — Downsampling factor

2 (default) | positive integer

The integer factor, K, by which to decrease the input sample rate.

Sample offset (0 to K-1) — Sample offset

0 (default) | integer

The Sample offset parameter delays the output samples by an integer number of sample periods, D, where 0 ≤ D ≤ (K–1), so that any of the K possible output phases can be selected. For example, when you downsample the sequence 1, 2, 3, ... by a factor of 4, you can select from four phases.

Input Sequence	Sample Offset, D	Output Sequence (K = 4)
1,2,3,...	0	1,5,9,13,17,21,25,29,...
1,2,3,...	1	0,2,6,10,14,18,22,26,...
1,2,3,...	2	0,3,7,11,15,19,23,27,...
1,2,3,...	3	0,4,8,12,16,20,24,28,...

The initial zero in each of the latter three output sequences in the table is a result of the default zero Initial conditions parameter setting for this example. See Latency for more information on the Initial conditions parameter.

Input processing — Method to process input

Columns as channels (frame based) (default) | Elements as channels (sample based)

Specify the method for input processing:

• Columns as channels (frame based) –– When you set the Input processing parameter to Columns as channels (frame based), the block treats each of the N input columns as an individual channel containing M_i sequential time samples. The block downsamples each channel independently by discarding K–1 rows of the input matrix following each row that it outputs.

  For more information, see What Is Frame-Based Processing?.

• Elements as channels (sample based) –– When you set the Input processing parameter to Elements as channels (sample based), the input can be an N-D array. The Downsample block treats each element of the input as a separate channel, and resamples each channel of the input over time. The block downsamples the input array by discarding K–1 samples following each sample that it passes through to the output. The input and output sizes of the Downsample block are identical.

  For more information, see What Is Sample-Based Processing?.

Rate options — Enforce single-rate or allow multirate processing

Enforce single-rate processing (default) | Allow multirate processing

Specify the method by which the block adjusts the rate at the output to accommodate the reduced number of samples. . You can select one of the following options. The behavior of these options depends on whether the Input processing parameter is set to Elements as channels (sample based) (sample-based processing mode) or Columns as channels (frame based) (frame-based processing mode).

• Elements as channels (sample based)

  • Enforce single-rate processing

    The block forces the output sample rate to match the input sample rate (T_so = T_si) by repeating every Kth input sample K times at the output. In this mode, the behavior of the block is similar to the operation of a Sample and Hold block with a repeating trigger event of period KT_si.

  • Allow multirate processing

    The sample period of the output is K times longer than the input sample period (T_so = KT_si).

• Columns as channels (frame based)

  • Enforce single rate processing

    The block generates the output at the slower (downsampled) rate using a proportionally smaller frame size than the input. For downsampling by a factor of K, the output frame size is K times smaller than the input frame size (M_o = M_i/K), but the input and output frame rates are equal.

    The ex_downsample_ref2 model shows a single-channel input with a frame size of 64 being downsampled by a factor of 4 to a frame size of 16. The input and output frame rates are identical.

    

  • Allow multirate processing

    The block generates the output at the slower (downsampled) rate by using a proportionally longer frame period at the output port than at the input port. For downsampling by a factor of K, the output frame period is K times longer than the input frame period (T_fo = KT_fi), but the input and output frame sizes are equal.

    The ex_downsample_ref1 model shows a single-channel input with a frame period of 1 second being downsampled by a factor of 4 to a frame period of 4 seconds. The input and output frame sizes are identical.

    

Initial conditions — Initial value

0 (default) | real scalar | array

The initial block value for cases of nonzero latency. You can specify a scalar or an array of the same size as the input.

Dependencies

This parameter appears only when you set the Rate options parameter to Allow multirate processing.

Model Examples

Acoustic Noise Cancellation (LMS)

Use the Least Mean Square (LMS) algorithm to subtract noise from an input signal. The LMS adaptive filter uses the reference signal on the Input port and the desired signal on the Desired port to automatically match the filter response. As it converges to the correct filter model, the filtered noise is subtracted and the error signal should contain only the original signal.

Open Model

Downsample a Signal

Downsampling operation on a signal with one-frame latency.

Open Model

Block Characteristics

Data Types	double | single | Boolean | base integer | fixed point
Direct Feedthrough	No
Multidimensional Signals	No
Variable-Size Signals	No
Zero-Crossing Detection	No

More About

Latency

Latency is the delay, measured in samples or frames, between the input and the output of the block.

The Downsample block has zero-tasking latency in the following cases:

• The Downsample factor parameter, K, is 1.

• The Input processing parameter is set to Columns as channels (frame based), and the Rate options parameter is set to Enforce single-rate processing.

• The Input processing parameter is set to Columns as channels (frame based), the Rate options parameter is set to Allow multirate processing, the Sample offset parameter, D, is set to 0, and the input frame size is equal to 1.

• The Input processing parameter is set to Elements as channels (sample based), and the Sample offset parameter, D, is 0.

Zero-tasking latency means that the block propagates input sample D+1 (received at t = 0) as the first output sample, followed by input sample D+1+K, input sample D+1+2K, and so on. When there is zero-tasking latency, the block ignores the value of the Initial conditions parameter.

In all other cases, the latency is nonzero:

• When the Input processing parameter is set to Elements as channels (sample based), the latency is one sample.

• When the Input processing parameter is set to Columns as channels (frame based) and the input frame size is greater than one, the latency is one frame.

In all cases of one-sample latency, the initial condition for each channel appears as the first output sample. Input sample D+1 appears as the second output sample for each channel, followed by input sample D+1+K, input sample D+1+2K, and so on. The Initial conditions parameter can be an array of the same size as the input or a scalar to be applied to all signal channels.

In all cases of one-frame latency, the M_i rows of the initial condition matrix appear in sequence as the first M_i output rows. Input sample D+1 (row D+1 of the input matrix) appears in the output as sample M_i+1, followed by input sample D+1+K, input sample D+1+2K, and so on. The Initial conditions value can be an M_i-by-N matrix containing one value for each channel or a scalar to be repeated across all elements of the M_i-by-N matrix.

Note

For more information on latency and the Simulink^® tasking modes, see Excess Algorithmic Delay (Tasking Latency) and Time-Based Scheduling and Code Generation (Simulink Coder).

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using Simulink® Coder™.

Generated code relies on memcpy or memset functions (string.h) under certain conditions.

HDL Code Generation

Generate Verilog and VHDL code for FPGA and ASIC designs using HDL Coder™.

HDL Coder™ provides additional configuration options that affect HDL implementation and synthesized logic.

Best Practices

It is good practice to follow the Downsample block with a unit delay. Doing so prevents the code generator from inserting an extra bypass register in the HDL code.

See also Multirate Model Requirements for HDL Code Generation (HDL Coder).

HDL Architecture

This block has a single, default HDL architecture.

HDL Block Properties

ConstrainedOutputPipeline	Number of registers to place at the outputs by moving existing delays within your design. Distributed pipelining does not redistribute these registers. The default is 0. For more details, see ConstrainedOutputPipeline (HDL Coder).
InputPipeline	Number of input pipeline stages to insert in the generated code. Distributed pipelining and constrained output pipelining can move these registers. The default is 0. For more details, see InputPipeline (HDL Coder).
OutputPipeline	Number of output pipeline stages to insert in the generated code. Distributed pipelining and constrained output pipelining can move these registers. The default is 0. For more details, see OutputPipeline (HDL Coder).

Complex Data Support

This block supports code generation for complex signals.

Restrictions

• Input processing set to Columns as channels (frame based) is not supported.

• For Input processing set to Elements as channels (sample based), select Allow multirate processing. With this setting, if Sample offset is set to 0, Initial conditions has no effect on generated code.

Fixed-Point Conversion
Design and simulate fixed-point systems using Fixed-Point Designer™.