# Zero Forcing Equalizer in ISI channel

I'm studying on designing 9-tap zero forcing equalizer to remove ISI in the channel. I assumed that the channel response is $$h[n] = [0.41, 0.815, 0.41]$$ and I tried to calculate bit error rate. When I choose $$h[n]=[0.21, 0.815, 0.21]$$ for example, I get good results. BER goes to 1e-4 for high SNR values. But the code below gives bit error rate of 0.5 when the channel response is $$[0.41, 0.815, 0.41]$$. Can anybody help me about this problem? I did something wrong but I couldn't find it.

N  = 10^4; % number of bits or symbols
Eb_N0_dB = [0:2:10]; % multiple Eb/N0 values

for ii = 1:length(Eb_N0_dB)

% Transmitter
ip = rand(1,N)>0.5; % generating 0,1 with equal probability
s = 2*ip-1; % BPSK modulation 0 -> -1; 1 -> 1

% Channel model, multipath channel
ht = [0.41 0.815 0.41]

chanOut = conv(s,ht);
n = 1/sqrt(2)*[randn(1,N+length(ht)-1) + j*randn(1,N+length(ht)-1)]; % white gaussian noise, 0dB variance

y = chanOut + 10^(-Eb_N0_dB(ii)/20)*n; % additive white gaussian noise

kk=4; % 9-tap filter
L  = length(ht);
hM = toeplitz([ht([2:end]) zeros(1,2*kk+1-L+1)], [ ht([2:-1:1]) zeros(1,2*kk+1-L+1) ]);
d  = zeros(1,2*kk+1);
d(kk+1) = 1;
c  = [inv(hM)*d.'].';

% matched filter
yFilt = conv(y,c);
yFilt = yFilt(kk+2:end);
yFilt = conv(yFilt,ones(1,1)); % convolution
ySamp = yFilt(1:1:N);  % sampling at time T

% receiver - hard decision decoding
ipHat = real(ySamp)>0;

%     % counting the errors
nErr(1,ii) = size(find([ip-ipHat]),2);
end

simBer = nErr/N; % simulated ber