Integrate and Dump

Integrate discrete-time signal with periodic resets

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Libraries:
Communications Toolbox / Comm Filters

Description

The Integrate and Dump block creates a cumulative sum of the discrete-time input signal, while resetting the sum to zero according to a fixed schedule. When the simulation begins, the block discards the number of samples specified in the Offset (number of samples) parameter. After the initial offset, the block sums the input signal along columns and resets the sum to zero every N input samples, where N is the Integration period (number of samples) parameter value. The reset occurs after the block produces its output at that time step. For more information, see More About.

Receiver models often use the integrate-and-dump operation to receive simple square-pulse transmissions. Fiber optics and spread-spectrum communications systems also use the integrate-and-dump operation.

Examples

Integrate and Dump Filtering of Noisy Pulses

Apply the integrate-and-dump filter with an integration period of 20 samples to noisy random binary data.

The cm_int_dump_filtering model upsamples BPSK modulated random binary data, adds noise to the data, and then applies integrate-and-dump filtering. A timescope plots the real component of samples for a frame of the transmitted random integer data (tx) and the received data after integrate and dump filtering (rx).

Ports

Input

In — Input signal

scalar | column vector | matrix

Input signal, specified as a scalar, column vector, or matrix. Nonscalar input signals must consist of one or more columns with (k×N) rows. The block treats each column as an independent channel, performing integration along each column. k is a positive integer and N is the value of Integration period (number of samples).

This port is unnamed on the block.

Data Types: single | double | int8 | int16 | int32 | uint8 | uint16 | uint32 | Boolean

Output

Out — Output signal

column vector | matrix

Output signal, returned as a column vector or matrix. The number of rows in the output signal varies based on the value assigned to Output intermediate values parameter.

This port is unnamed on the block.

Parameters

To edit block parameters interactively, use the Property Inspector. From the Simulink^® Toolstrip, on the Simulation tab, in the Prepare gallery, select Property Inspector.

Main

Integration period (number of samples) — Number of input samples between resets

8 (default) | integer in the range [2, ∞)

Number of input samples between resets, specified as an integer in the range [2, ∞).

Offset (number of samples) — Number of input samples to discard

0 (default) | scalar | vector

Number of input samples to discard from each column of input data at the beginning of the simulation, specified as a nonnegative integer scalar or vector. When you set this parameter to a nonzero value, the block outputs zeros in place of the discarded initial input samples.

• When you specify this parameter as a vector of length L, each element of the vector represents the number of samples to discard from the corresponding channel (column) of the input data matrix. The length of the vector L must match the number of columns in the input data matrix.

• When you specify this property as a scalar value, the block applies the same offset value to each column of the input data matrix. The offset creates a transient effect, rather than a persistent delay.

Output intermediate values — Option to output intermediate cumulative sums

off (default) | on

Select this parameter to output intermediate cumulative sums between successive resets.

• If you clear the check box (off), then the block outputs the cumulative sum at each reset time.

  • If the input is a scalar value, then the output sample time is N times the input sample time and the block experiences a delay whose duration is one output sample period. In this case, the output dimensions match the input dimensions.

  • If the input is a (k×N)-by-L matrix, then the output is k-by-L. In this case, the block experiences no delay and the output period matches the input period.

• If you select the check box (on), then the block outputs the cumulative sum at each time step. The output has the same sample time and the same matrix dimensions as the input.

Fixed-Point Attributes

The settings for the following parameters apply only when block inputs are fixed-point signals.

Data Types

Rounding mode — Rounding mode for fixed-point operations

Floor (default) | Ceiling | Convergent | Nearest | Round | Simplest | Zero

Select the rounding mode for fixed-point operations. The block uses rounding mode when the result of a fixed-point calculation does not map exactly to a number representable by the data type. For more information, see Rounding Modes or Use Simplest Rounding for Efficient Generated Code (Fixed-Point Designer).

Saturate on integer overflow — Overflow mode for fixed-point operations

off (default) | on

Use this parameter to specify the overflow mode to be used if the magnitude of a fixed-point calculation result does not fit into the range of the data type and scaling that stores the result.

• When you clear the check box (off), the fixed-point calculation wraps on overflow. The wrap uses modulo arithmetic to cast an overflow back into the representable range of the data type. For more information, see Modulo Arithmetic (Fixed-Point Designer).

• When you select the check box (on), the fixed-point calculation saturates on overflow. The saturation represents positive overflows as the largest positive number in the range being used, and negative overflows as the largest negative number in the range being used.

Accumulator — Accumulator data type

Inherit: Inherit via internal rule (default) | Inherit: Same as input | fixdt(1,16,0)

Specify the accumulator word and fraction lengths. For diagrams showing the use of the accumulator data type in this block, see the filter structure diagrams for the Discrete FIR Filter (Simulink) block and Multiplication Data Types.

• When you select Inherit: Inherit via internal rule, the block inherits the data type based on an internal rule. For more information on this rule, see Inherit via Internal Rule.

• When you select Inherit: Same as input, these characteristics match those of the input to the block.

• When you select Binary point scaling, enter the word length and the fraction length of the output, in bits.

For information about specifying data types, see Data Type Assistant.

Output — Output data type

Inherit: Same as accumulator (default) | Inherit: Same as input | fixdt(1,16,0)

Specify the output word and fraction lengths.

• When you select Inherit: Same as input, these characteristics match those of the input to the block.

• When you select Inherit: Same as accumulator, these characteristics match those of the accumulator.

• When you select Binary point scaling, enter the word length and the fraction length of the output, in bits.

For information about specifying data types, see Data Type Assistant.

Block Characteristics

Data Types	double | fixed point | single
Multidimensional Signals	no
Variable-Size Signals	no

More About

Transients and Delays

A nonzero value in the Offset parameter causes the block to output one or more zeros during the initial period while it discards input samples. If the input is a matrix with n columns and the Offset parameter is a length-n vector, then the m^th element of the Offset vector is the offset for the m^th column of data. If Offset is a scalar, then the block applies the same offset to each column of data. The output of initial zeros due to a nonzero Offset value is a transient effect, not a persistent delay.

When you clear Output intermediate values, the block delays its output, relative to its input, throughout the simulation:

• If the input is a scalar value, then the output is delayed by one sample after any transient effect is over. That is, after removing transients from the input and output, you can see the result of the m^th integration period in the output sample indexed by m+1.

• If the input is a column vector or matrix and the Offset parameter is nonzero, then after the transient effect is over, the result of each integration period appears in the output frame corresponding to the last input sample of that integration period. In cases where an integration period spans two input frames, the offset is one frame later than the output frame corresponding to the first input sample of that integration period.

Example of Transient and Delay Effect

This image illustrates a transient effect for three output samples and a one-sample delay for output samples from the block. The figure also indicates how the input and output values are organized as column vectors. For each vector in the figure:

• Discarded input samples are white

• Last samples of integration periods are underlined

• Transient zeros in the output are white

.

The transient effect lasts for ceil(13/5) output samples because the block discards 13 input samples and the integration period is 5. The first output sample after the transient effect is over, 80, corresponds to the sum 14+15+16+17+18 and appears at the time of the input sample 18. The next output sample, 105, corresponds to the sum 19+20+21+22+23 and appears at the time of the input sample 23. Notice that the input sample 23 is one frame later than the input sample 19; that is, this five-sample integration period spans two input frames. As a result, the output of 105 is delayed compared to the first input (19) that contributes to that sum.

Operating Scenarios

If you set Integration period (number of samples) to 4 and Offset (number of samples) to the scalar 3, this table shows the block the first several output values for an input ramp signal (1, 2, 3, 4, ...) depending on the Output intermediate values check box setting and the input signal properties. The values in the table do not reflect vector sizes but merely indicate numerical values. In all cases, the block discards the first three input samples (1, 2, and 3).

Check Box	Input Signal Properties	First Several Output Values
Cleared	Scalar	0, 0, 4+5+6+7, and 8+9+10+11, where one 0 is an initial transient value and the other 0 is a delay value that results from the cleared check box and scalar value input.
Cleared	Column vector of length 4	0, 4+5+6+7, and 8+9+10+11, where 0 is an initial delay value that results from the nonzero offset. The output is a scalar value.
Selected	Scalar	0, 0, 0, 4, 4+5, 4+5+6, 4+5+6+7, 8, 8+9, 8+9+10, 8+9+10+11, and 12, where the three 0s are initial transient values.
Selected	Column vector of length 4	0, 0, 0, 4, 4+5, 4+5+6, 4+5+6+7, 8, 8+9, 8+9+10, 8+9+10+11, and 12, where the three 0s are initial transient values. The output is a column vector of length 4.

Fixed-Point Signal Flow

Floating-point inheritance takes precedence over the data type settings. When the block input is floating point, all block data types match the input. When the block input is fixed point, all internal data types are signed fixed point.

For more information about the parameters pertaining to fixed-point applications, see Specify Fixed-Point Attributes for Blocks.

Data Type Assistant

The Data Type Assistant helps you set data attributes. To use the Data Type Assistant, click . For more information, see Specify Data Types Using Data Type Assistant (Simulink).

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

Version History

Introduced before R2006a